-
1
-
-
84953339870
-
Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: a review
-
Abdullah SS, Malek MA (2016) Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: a review. Int J Water 10:55–66. doi:10.1504/IJW.2016.073741
-
(2016)
Int J Water
, vol.10
, pp. 55-66
-
-
Abdullah, S.S.1
Malek, M.A.2
-
2
-
-
0034254196
-
Comparing neural network and autoregressive moving average techniques for the provision of continuous river flow forecasts in two contrasting catchments
-
Abrahart RJ, See L (2000) Comparing neural network and autoregressive moving average techniques for the provision of continuous river flow forecasts in two contrasting catchments. Hydrol Process 14:2157–2172. doi:10.1002/1099-1085(20000815/30)14:11/12<2157::AID-HYP57>3.0.CO;2-S
-
(2000)
Hydrol Process
, vol.14
, pp. 2157-2172
-
-
Abrahart, R.J.1
See, L.2
-
4
-
-
84863764389
-
Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting
-
Abrahart RJ, Anctil F, Coulibaly P et al (2012) Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting. Prog Phys Geogr 36:480–513. doi:10.1177/0309133312444943
-
(2012)
Prog Phys Geogr
, vol.36
, pp. 480-513
-
-
Abrahart, R.J.1
Anctil, F.2
Coulibaly, P.3
-
5
-
-
78651472663
-
Modeling of daily pan evaporation using partial least squares regression
-
Abudu S, Cui C, King JP et al (2011) Modeling of daily pan evaporation using partial least squares regression. Sci China Technol Sci 54:163–174. doi:10.1007/s11431-010-4205-z
-
(2011)
Sci China Technol Sci
, vol.54
, pp. 163-174
-
-
Abudu, S.1
Cui, C.2
King, J.P.3
-
6
-
-
80052027629
-
A wavelet neural network conjunction model for groundwater level forecasting
-
Adamowski J, Chan HF (2011) A wavelet neural network conjunction model for groundwater level forecasting. J Hydrol 407:28–40. doi:10.1016/j.jhydrol.2011.06.013
-
(2011)
J Hydrol
, vol.407
, pp. 28-40
-
-
Adamowski, J.1
Chan, H.F.2
-
7
-
-
77955276087
-
Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds
-
Adamowski J, Sun K (2010) Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds. J Hydrol 390:85–91. doi:10.1016/j.jhydrol.2010.06.033
-
(2010)
J Hydrol
, vol.390
, pp. 85-91
-
-
Adamowski, J.1
Sun, K.2
-
8
-
-
67349276109
-
The relative utility of regression and artificial neural networks models for rapidly predicting the capacity of water supply reservoirs
-
Adeloye A (2009) The relative utility of regression and artificial neural networks models for rapidly predicting the capacity of water supply reservoirs. Environ Model Softw 24:1233–1240. doi:10.1016/j.envsoft.2009.04.002
-
(2009)
Environ Model Softw
, vol.24
, pp. 1233-1240
-
-
Adeloye, A.1
-
9
-
-
33744900877
-
Artificial neural network based generalized storage-yield-reliability models using the Levenberg-Marquardt algorithm
-
Adeloye AJ, De Munari A (2006) Artificial neural network based generalized storage-yield-reliability models using the Levenberg-Marquardt algorithm. J Hydrol 326:215–230. doi:10.1016/j.jhydrol.2005.10.033
-
(2006)
J Hydrol
, vol.326
, pp. 215-230
-
-
Adeloye, A.J.1
De Munari, A.2
-
10
-
-
84925489228
-
ANN based sediment prediction model utilizing different input scenarios
-
Afan HA, El-Shafie A, Yaseen ZM et al (2014) ANN based sediment prediction model utilizing different input scenarios. Water Resour Manag 29:1231–1245. doi:10.1007/s11269-014-0870-1
-
(2014)
Water Resour Manag
, vol.29
, pp. 1231-1245
-
-
Afan, H.A.1
El-Shafie, A.2
Yaseen, Z.M.3
-
11
-
-
84864370476
-
Modeling and forecasting river flow rate from the Melen Watershed, Turkey
-
Akiner ME, Akkoyunlu A (2012) Modeling and forecasting river flow rate from the Melen Watershed, Turkey. J Hydrol 456–457:121–129. doi:10.1016/j.jhydrol.2012.06.031
-
(2012)
J Hydrol
, vol.456-457
, pp. 121-129
-
-
Akiner, M.E.1
Akkoyunlu, A.2
-
12
-
-
77949266538
-
A multi-objective memetic and hybrid methodology for optimizing the parameters and performance of artificial neural networks
-
Almeida LM, Ludermir TB (2010) A multi-objective memetic and hybrid methodology for optimizing the parameters and performance of artificial neural networks. Neurocomputing 73:1438–1450
-
(2010)
Neurocomputing
, vol.73
, pp. 1438-1450
-
-
Almeida, L.M.1
Ludermir, T.B.2
-
13
-
-
33749443208
-
Suspended sediment load simulation by two artificial neural network methods using hydrometeorological data
-
Alp M, Cigizoglu H (2007) Suspended sediment load simulation by two artificial neural network methods using hydrometeorological data. Environ Model Softw 22:2–13. doi:10.1016/j.envsoft.2005.09.009
-
(2007)
Environ Model Softw
, vol.22
, pp. 2-13
-
-
Alp, M.1
Cigizoglu, H.2
-
14
-
-
78650584376
-
Fuzzy neural networks for water level and discharge forecasting with uncertainty
-
Alvisi S, Franchini M (2011) Fuzzy neural networks for water level and discharge forecasting with uncertainty. Environ Model Softw 26:523–537. doi:10.1016/j.envsoft.2010.10.016
-
(2011)
Environ Model Softw
, vol.26
, pp. 523-537
-
-
Alvisi, S.1
Franchini, M.2
-
15
-
-
38949193150
-
Monthly streamflow prediction in the Volta Basin of West Africa: a SISO NARMAX polynomial modelling
-
Amisigo BA, van de Giesen N, Rogers C et al (2008) Monthly streamflow prediction in the Volta Basin of West Africa: a SISO NARMAX polynomial modelling. Phys Chem Earth A B C 33:141–150. doi:10.1016/j.pce.2007.04.019
-
(2008)
Phys Chem Earth A B C
, vol.33
, pp. 141-150
-
-
Amisigo, B.A.1
van de Giesen, N.2
Rogers, C.3
-
16
-
-
1442291113
-
Impact of the length of observed records on the performance of ANN and of conceptual parsimonious rainfall-runoff forecasting models
-
Anctil F, Perrin C, Andréassian V (2004) Impact of the length of observed records on the performance of ANN and of conceptual parsimonious rainfall-runoff forecasting models. Environ Model Softw 19:357–368. doi:10.1016/S1364-8152(03)00135-X
-
(2004)
Environ Model Softw
, vol.19
, pp. 357-368
-
-
Anctil, F.1
Perrin, C.2
Andréassian, V.3
-
17
-
-
33645158824
-
Rainfall–runoff modelling using artificial neural networks technique: a Blue Nile catchment case study
-
Antar MA, Elassiouti I, Allam MN (2006) Rainfall–runoff modelling using artificial neural networks technique: a Blue Nile catchment case study. Hydrol Process 20:1201–1216
-
(2006)
Hydrol Process
, vol.20
, pp. 1201-1216
-
-
Antar, M.A.1
Elassiouti, I.2
Allam, M.N.3
-
18
-
-
33947572974
-
A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff
-
Aqil M, Kita I, Yano A, Nishiyama S (2007) A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff. J Hydrol 337:22–34. doi:10.1016/j.jhydrol.2007.01.013
-
(2007)
J Hydrol
, vol.337
, pp. 22-34
-
-
Aqil, M.1
Kita, I.2
Yano, A.3
Nishiyama, S.4
-
19
-
-
80052021232
-
Application of artificial neural network ensembles in probabilistic hydrological forecasting
-
Araghinejad S, Azmi M, Kholghi M (2011) Application of artificial neural network ensembles in probabilistic hydrological forecasting. J Hydrol 407:94–104. doi:10.1016/j.jhydrol.2011.07.011
-
(2011)
J Hydrol
, vol.407
, pp. 94-104
-
-
Araghinejad, S.1
Azmi, M.2
Kholghi, M.3
-
20
-
-
84884167501
-
A new hybrid artificial neural networks for rainfall-runoff process modeling
-
Asadi S, Shahrabi J, Abbaszadeh P, Tabanmehr S (2013) A new hybrid artificial neural networks for rainfall-runoff process modeling. Neurocomputing 121:470–480. doi:10.1016/j.neucom.2013.05.023
-
(2013)
Neurocomputing
, vol.121
, pp. 470-480
-
-
Asadi, S.1
Shahrabi, J.2
Abbaszadeh, P.3
Tabanmehr, S.4
-
21
-
-
85027938529
-
River discharges forecasting in Northern Iraq using different ANN techniques
-
Awchi TA (2014) River discharges forecasting in Northern Iraq using different ANN techniques. Water Resour Manag 1–14. doi: 10.1007/s11269-014-0516-3
-
(2014)
Water Resour Manag
, pp. 1-14
-
-
Awchi, T.A.1
-
22
-
-
58149472216
-
Design of experiments on neural network’s training for nonlinear time series forecasting
-
Balestrassi PP, Popova E, Paiva AP, Marangon Lima JW (2009) Design of experiments on neural network’s training for nonlinear time series forecasting. Neurocomputing 72:1160–1178. doi:10.1016/j.neucom.2008.02.002
-
(2009)
Neurocomputing
, vol.72
, pp. 1160-1178
-
-
Balestrassi, P.P.1
Popova, E.2
Paiva, A.P.3
Marangon Lima, J.W.4
-
23
-
-
84864856143
-
Estimation of suspended sediment concentration from turbidity measurements using artificial neural networks
-
Bayram A, Kankal M, Onsoy H (2012) Estimation of suspended sediment concentration from turbidity measurements using artificial neural networks. Environ Monit Assess 184:4355–4365. doi:10.1007/s10661-011-2269-2
-
(2012)
Environ Monit Assess
, vol.184
, pp. 4355-4365
-
-
Bayram, A.1
Kankal, M.2
Onsoy, H.3
-
24
-
-
84900639299
-
Prediction of suspended sediment concentration from water quality variables
-
Bayram A, Kankal M, Tayfur G, Önsoy H (2013) Prediction of suspended sediment concentration from water quality variables. Neural Comput Applic 24:1079–1087. doi:10.1007/s00521-012-1333-3
-
(2013)
Neural Comput Applic
, vol.24
, pp. 1079-1087
-
-
Bayram, A.1
Kankal, M.2
Tayfur, G.3
Önsoy, H.4
-
25
-
-
0345257361
-
Short-term water level prediction using neural networks and neuro-fuzzy approach
-
Bazartseren B, Hildebrandt G, Holz K-P (2003) Short-term water level prediction using neural networks and neuro-fuzzy approach. Neurocomputing 55:439–450. doi:10.1016/S0925-2312(03)00388-6
-
(2003)
Neurocomputing
, vol.55
, pp. 439-450
-
-
Bazartseren, B.1
Hildebrandt, G.2
Holz, K.-P.3
-
26
-
-
0036825531
-
Learning long-term dependencies by the selective addition of time-delayed connections to recurrent neural networks
-
Boné R, Crucianu M, Asselin de Beauville JP (2002) Learning long-term dependencies by the selective addition of time-delayed connections to recurrent neural networks. Neurocomputing 48:251–266. doi:10.1016/S0925-2312(01)00654-3
-
(2002)
Neurocomputing
, vol.48
, pp. 251-266
-
-
Boné, R.1
Crucianu, M.2
Asselin de Beauville, J.P.3
-
27
-
-
10644295753
-
Input determination for neural network models in water resources applications. Part 1 - Background and methodology
-
Bowden GJ, Dandy GC, Maier HR (2005) Input determination for neural network models in water resources applications. Part 1 - Background and methodology. J Hydrol 301:75–92. doi:10.1016/j.jhydrol.2004.06.021
-
(2005)
J Hydrol
, vol.301
, pp. 75-92
-
-
Bowden, G.J.1
Dandy, G.C.2
Maier, H.R.3
-
29
-
-
0034163592
-
Estimating daily pan evaporation with artificial neural networks
-
Bruton JM, McClendon RW, Hoogenboom G (2000) Estimating daily pan evaporation with artificial neural networks. Trans ASAE 43:491–496. doi:10.13031/2013.2730
-
(2000)
Trans ASAE
, vol.43
, pp. 491-496
-
-
Bruton, J.M.1
McClendon, R.W.2
Hoogenboom, G.3
-
30
-
-
0036499322
-
Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural network models
-
Cannon AJ, Whitfield PH (2002) Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural network models. J Hydrol 259:136–151. doi:10.1016/S0022-1694(01)00581-9
-
(2002)
J Hydrol
, vol.259
, pp. 136-151
-
-
Cannon, A.J.1
Whitfield, P.H.2
-
31
-
-
84954358683
-
Jordan recurrent neural network versus IHACRES in modelling daily streamflows
-
Carcano EC, Bartolini P, Muselli M, Piroddi L (2008) Jordan recurrent neural network versus IHACRES in modelling daily streamflows. J Hydrol 362:291–307. doi:10.1016/j.jhydrol.2008.08.026
-
(2008)
J Hydrol
, vol.362
, pp. 291-307
-
-
Carcano, E.C.1
Bartolini, P.2
Muselli, M.3
Piroddi, L.4
-
32
-
-
17144442570
-
Modelling of the monthly and daily behaviour of the runoff of the Xallas river using Box–Jenkins and neural networks methods
-
Castellano-Méndez M, González-Manteiga W, Febrero-Bande M et al (2004) Modelling of the monthly and daily behaviour of the runoff of the Xallas river using Box–Jenkins and neural networks methods. J Hydrol 296:38–58. doi:10.1016/j.jhydrol.2004.03.011
-
(2004)
J Hydrol
, vol.296
, pp. 38-58
-
-
Castellano-Méndez, M.1
González-Manteiga, W.2
Febrero-Bande, M.3
-
33
-
-
0035340711
-
A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction
-
Chang FJ, Chen YC (2001) A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction. J Hydrol 245:153–164. doi:10.1016/S0022-1694(01)00350-X
-
(2001)
J Hydrol
, vol.245
, pp. 153-164
-
-
Chang, F.J.1
Chen, Y.C.2
-
34
-
-
31044455061
-
Integration of artificial neural networks with conceptual models in rainfall-runoff modeling
-
Chen J, Adams BJ (2006) Integration of artificial neural networks with conceptual models in rainfall-runoff modeling. J Hydrol 318:232–249. doi:10.1016/j.jhydrol.2005.06.017
-
(2006)
J Hydrol
, vol.318
, pp. 232-249
-
-
Chen, J.1
Adams, B.J.2
-
35
-
-
60549091177
-
Evolutionary artificial neural networks for hydrological systems forecasting
-
Chen YH, Chang FJ (2009) Evolutionary artificial neural networks for hydrological systems forecasting. J Hydrol 367:125–137. doi:10.1016/j.jhydrol.2009.01.009
-
(2009)
J Hydrol
, vol.367
, pp. 125-137
-
-
Chen, Y.H.1
Chang, F.J.2
-
36
-
-
52949137358
-
A new indirect multi-step-ahead prediction model for a long-term hydrologic prediction
-
Cheng CT, Xie JX, Chau KW, Layeghifard M (2008) A new indirect multi-step-ahead prediction model for a long-term hydrologic prediction. J Hydrol 361:118–130. doi:10.1016/j.jhydrol.2008.07.040
-
(2008)
J Hydrol
, vol.361
, pp. 118-130
-
-
Cheng, C.T.1
Xie, J.X.2
Chau, K.W.3
Layeghifard, M.4
-
37
-
-
1842426595
-
Comparison of static-feedforward and dynamic-feedback neural networks for rainfall-runoff modeling
-
Chiang YM, Chang LC, Chang FJ (2004) Comparison of static-feedforward and dynamic-feedback neural networks for rainfall-runoff modeling. J Hydrol 290:297–311. doi:10.1016/j.jhydrol.2003.12.033
-
(2004)
J Hydrol
, vol.290
, pp. 297-311
-
-
Chiang, Y.M.1
Chang, L.C.2
Chang, F.J.3
-
38
-
-
0034847598
-
A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process
-
Choi DJ, Park H (2001) A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process. Water Res 35:3959–3967. doi:10.1016/S0043-1354(01)00134-8
-
(2001)
Water Res
, vol.35
, pp. 3959-3967
-
-
Choi, D.J.1
Park, H.2
-
39
-
-
11044233103
-
Hybrid neural network—finite element river flow model
-
Chua LH, Holz K-P (2005) Hybrid neural network—finite element river flow model. J Hydraul Eng 131:52–59
-
(2005)
J Hydraul Eng
, vol.131
, pp. 52-59
-
-
Chua, L.H.1
Holz, K.-P.2
-
40
-
-
78651378958
-
Runoff forecasting for an asphalt plane by Artificial Neural Networks and comparisons with kinematic wave and autoregressive moving average models
-
Chua LHC, Wong TSW (2011) Runoff forecasting for an asphalt plane by Artificial Neural Networks and comparisons with kinematic wave and autoregressive moving average models. J Hydrol 397:191–201. doi:10.1016/j.jhydrol.2010.11.030
-
(2011)
J Hydrol
, vol.397
, pp. 191-201
-
-
Chua, L.H.C.1
Wong, T.S.W.2
-
41
-
-
27544493548
-
Generalized regression neural network in modelling river sediment yield
-
Cigizoglu HK, Alp M (2006) Generalized regression neural network in modelling river sediment yield. Adv Eng Softw 37:63–68. doi:10.1016/j.advengsoft.2005.05.002
-
(2006)
Adv Eng Softw
, vol.37
, pp. 63-68
-
-
Cigizoglu, H.K.1
Alp, M.2
-
42
-
-
60549084178
-
Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data
-
Cobaner M, Unal B, Kisi O (2009) Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data. J Hydrol 367:52–61. doi:10.1016/j.jhydrol.2008.12.024
-
(2009)
J Hydrol
, vol.367
, pp. 52-61
-
-
Cobaner, M.1
Unal, B.2
Kisi, O.3
-
43
-
-
34249885607
-
Knowledge-based modularization and global optimization of artificial neural network models in hydrological forecasting
-
Corzo G, Solomatine D (2007) Knowledge-based modularization and global optimization of artificial neural network models in hydrological forecasting. Neural Netw 20:528–536. doi:10.1016/j.neunet.2007.04.019
-
(2007)
Neural Netw
, vol.20
, pp. 528-536
-
-
Corzo, G.1
Solomatine, D.2
-
44
-
-
0032829433
-
Hydrological forecasting with artificial neural networks: The state of the art
-
Coulibaly P, Anctil F, Bobee B (1999) Hydrological forecasting with artificial neural networks: The state of the art. Can J Civ Eng 26:293–304
-
(1999)
Can J Civ Eng
, vol.26
, pp. 293-304
-
-
Coulibaly, P.1
Anctil, F.2
Bobee, B.3
-
45
-
-
0034621379
-
Daily reservoir inflow forecasting using artificial neural networks with stopped training approach
-
Coulibaly P, Anctil F, Bobée B (2000) Daily reservoir inflow forecasting using artificial neural networks with stopped training approach. J Hydrol 230:244–257. doi:10.1016/S0022-1694(00)00214-6
-
(2000)
J Hydrol
, vol.230
, pp. 244-257
-
-
Coulibaly, P.1
Anctil, F.2
Bobée, B.3
-
46
-
-
0034749335
-
Hydrological modelling using artificial neural networks
-
Dawson CW, Wilby RL (2001) Hydrological modelling using artificial neural networks. Prog Phys Geogr 25:80–108. doi:10.1177/030913330102500104
-
(2001)
Prog Phys Geogr
, vol.25
, pp. 80-108
-
-
Dawson, C.W.1
Wilby, R.L.2
-
47
-
-
0027470319
-
A verification of some methods to determine the fluxes of momentum, sensible heat, and water vapour using standard deviation and structure parameter of scalar meteorological quantities
-
De Bruin HAR, Kohsiek W, Van Den Hurk BJJM (1993) A verification of some methods to determine the fluxes of momentum, sensible heat, and water vapour using standard deviation and structure parameter of scalar meteorological quantities. Bound-Lay Meteorol 63:231–257. doi:10.1007/BF00710461
-
(1993)
Bound-Lay Meteorol
, vol.63
, pp. 231-257
-
-
De Bruin, H.A.R.1
Kohsiek, W.2
Van Den Hurk, B.J.J.M.3
-
48
-
-
0027242791
-
Backpropagation neural nets with one and two hidden layers
-
de Villiers J, Barnard E (1993) Backpropagation neural nets with one and two hidden layers. IEEE Trans Neural Netw 4:136–141. doi:10.1109/72.182704
-
(1993)
IEEE Trans Neural Netw
, vol.4
, pp. 136-141
-
-
de Villiers, J.1
Barnard, E.2
-
49
-
-
53949114438
-
A hybrid ARIMA and artificial neural networks model to forecast particulate matter in urban areas: The case of Temuco, Chile
-
Díaz-Robles LA, Ortega JC, Fu JS et al (2008) A hybrid ARIMA and artificial neural networks model to forecast particulate matter in urban areas: The case of Temuco, Chile. Atmos Environ 42:8331–8340. doi:10.1016/j.atmosenv.2008.07.020
-
(2008)
Atmos Environ
, vol.42
, pp. 8331-8340
-
-
Díaz-Robles, L.A.1
Ortega, J.C.2
Fu, J.S.3
-
50
-
-
77953962223
-
Modelling of evaporation from the reservoir of Yuvacik dam using adaptive neuro-fuzzy inference systems
-
Dogan E, Gumrukcuoglu M, Sandalci M, Opan M (2010) Modelling of evaporation from the reservoir of Yuvacik dam using adaptive neuro-fuzzy inference systems. Eng Appl Artif Intell 23:961–967. doi:10.1016/j.engappai.2010.03.007
-
(2010)
Eng Appl Artif Intell
, vol.23
, pp. 961-967
-
-
Dogan, E.1
Gumrukcuoglu, M.2
Sandalci, M.3
Opan, M.4
-
52
-
-
78049362919
-
Comparison of three data-driven techniques in modelling the evapotranspiration process
-
El-Baroudy I, Elshorbagy A, Carey SK et al (2010) Comparison of three data-driven techniques in modelling the evapotranspiration process. J Hydroinform 12:365. doi:10.2166/hydro.2010.029
-
(2010)
J Hydroinform
, vol.12
, pp. 365
-
-
El-Baroudy, I.1
Elshorbagy, A.2
Carey, S.K.3
-
53
-
-
79952665438
-
Generalized versus non-generalized neural network model for multi-lead inflow forecasting at Aswan High Dam
-
El-Shafie A, Noureldin A (2011) Generalized versus non-generalized neural network model for multi-lead inflow forecasting at Aswan High Dam. Hydrol Earth Syst Sci 15:841–858. doi:10.5194/hess-15-841-2011
-
(2011)
Hydrol Earth Syst Sci
, vol.15
, pp. 841-858
-
-
El-Shafie, A.1
Noureldin, A.2
-
54
-
-
33947693294
-
A neuro-fuzzy model for inflow forecasting of the Nile river at Aswan high dam
-
El-Shafie A, Taha MR, Noureldin A (2007) A neuro-fuzzy model for inflow forecasting of the Nile river at Aswan high dam. Water Resour Manag 21:533–556
-
(2007)
Water Resour Manag
, vol.21
, pp. 533-556
-
-
El-Shafie, A.1
Taha, M.R.2
Noureldin, A.3
-
55
-
-
69249208624
-
Enhancing inflow forecasting model at aswan high dam utilizing radial basis neural network and upstream monitoring stations measurements
-
El-Shafie A, Abdin AE, Noureldin A, Taha MR (2009) Enhancing inflow forecasting model at aswan high dam utilizing radial basis neural network and upstream monitoring stations measurements. Water Resour Manag 23:2289–2315. doi:10.1007/s11269-008-9382-1
-
(2009)
Water Resour Manag
, vol.23
, pp. 2289-2315
-
-
El-Shafie, A.1
Abdin, A.E.2
Noureldin, A.3
Taha, M.R.4
-
56
-
-
77952881356
-
Neural network modeling of time-dependent creep deformations in masonry structures
-
El-Shafie A, Abdelazim T, Noureldin A (2010) Neural network modeling of time-dependent creep deformations in masonry structures. Neural Comput Applic 19:583–594
-
(2010)
Neural Comput Applic
, vol.19
, pp. 583-594
-
-
El-Shafie, A.1
Abdelazim, T.2
Noureldin, A.3
-
57
-
-
84859572047
-
Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia
-
El-Shafie A, Noureldin A, Taha M et al (2012a) Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia. Hydrol Earth Syst Sci 16:1151–1169. doi:10.5194/hess-16-1151-2012
-
(2012)
Hydrol Earth Syst Sci
, vol.16
, pp. 1151-1169
-
-
El-Shafie, A.1
Noureldin, A.2
Taha, M.3
-
58
-
-
84864077196
-
Radial basis function neural networks for reliably forecasting rainfall
-
El-Shafie AH, El-Shafie A, Almukhtar A et al (2012b) Radial basis function neural networks for reliably forecasting rainfall. J Water Clim Chan 3:125–138
-
(2012)
J Water Clim Chan
, vol.3
, pp. 125-138
-
-
El-Shafie, A.H.1
El-Shafie, A.2
Almukhtar, A.3
-
59
-
-
0037005708
-
Estimation of missing streamflow data using principles of chaos theory
-
Elshorbagy A, Simonovic SP, Panu US (2002) Estimation of missing streamflow data using principles of chaos theory. J Hydrol 255:123–133
-
(2002)
J Hydrol
, vol.255
, pp. 123-133
-
-
Elshorbagy, A.1
Simonovic, S.P.2
Panu, U.S.3
-
60
-
-
84861487810
-
Estimating Penman--Monteith reference evapotranspiration using artificial neural networks and genetic algorithm: a case study
-
Eslamian SS, Gohari SA, Zareian MJ, Firoozfar A (2012) Estimating Penman--Monteith reference evapotranspiration using artificial neural networks and genetic algorithm: a case study. Arab J Sci Eng 37:935–944
-
(2012)
Arab J Sci Eng
, vol.37
, pp. 935-944
-
-
Eslamian, S.S.1
Gohari, S.A.2
Zareian, M.J.3
Firoozfar, A.4
-
61
-
-
84888128953
-
Prediction and simulation of monthly groundwater levels by genetic programming
-
Fallah-Mehdipour E, Bozorg Haddad O, Mariño MA (2013) Prediction and simulation of monthly groundwater levels by genetic programming. J Hydro Environment Res 7:253–260. doi:10.1016/j.jher.2013.03.005
-
(2013)
J Hydro Environment Res
, vol.7
, pp. 253-260
-
-
Fallah-Mehdipour, E.1
Bozorg Haddad, O.2
Mariño, M.A.3
-
62
-
-
84880039120
-
Integrated Artificial Neural Network (ANN) and Stochastic Dynamic Programming (SDP) Model for Optimal Release Policy
-
Fayaed S, El-Shafie A, Jaafar O (2013) Integrated Artificial Neural Network (ANN) and Stochastic Dynamic Programming (SDP) Model for Optimal Release Policy. Water Resour Manag 27:3679–3696. doi:10.1007/s11269-013-0373-5
-
(2013)
Water Resour Manag
, vol.27
, pp. 3679-3696
-
-
Fayaed, S.1
El-Shafie, A.2
Jaafar, O.3
-
63
-
-
84877022172
-
Comparison of artificial neural networks and stochastic models in river discharge forecasting, (Case study: Ghara- Aghaj River, Fars Province, Iran)
-
Fereydooni M, Rahnemaei M, Babazadeh H et al (2012) Comparison of artificial neural networks and stochastic models in river discharge forecasting, (Case study: Ghara- Aghaj River, Fars Province, Iran). Afr J Agric Res 7:5446–5458. doi:10.5897/AJAR11.1091
-
(2012)
Afr J Agric Res
, vol.7
, pp. 5446-5458
-
-
Fereydooni, M.1
Rahnemaei, M.2
Babazadeh, H.3
-
64
-
-
77954386440
-
Monthly total sediment forecasting using adaptive neuro fuzzy inference system
-
Firat M, Güngör M (2010) Monthly total sediment forecasting using adaptive neuro fuzzy inference system. Stoch Env Res Risk A 24:259–270. doi:10.1007/s00477-009-0315-1
-
(2010)
Stoch Env Res Risk A
, vol.24
, pp. 259-270
-
-
Firat, M.1
Güngör, M.2
-
66
-
-
0031998129
-
Application example of neural networks for time series analysis: rainfall–runoff modeling
-
Furundzic D (1998) Application example of neural networks for time series analysis: rainfall–runoff modeling. Signal Process 64:383–396. doi:10.1016/S0165-1684(97)00203-X
-
(1998)
Signal Process
, vol.64
, pp. 383-396
-
-
Furundzic, D.1
-
67
-
-
57649235231
-
Continuous query scheduler based on operators clustering
-
Gao H, Zhang Z, Lai Y et al (2008) Continuous query scheduler based on operators clustering. J Cent South Univ Technol (Engl Ed) 15:830–834. doi:10.1007/s11771
-
(2008)
J Cent South Univ Technol (Engl Ed)
, vol.15
, pp. 830-834
-
-
Gao, H.1
Zhang, Z.2
Lai, Y.3
-
68
-
-
70350733507
-
Feature extraction for time-series data: An artificial neural network evolutionary training model for the management of mountainous watersheds
-
Glezakos TJ, Tsiligiridis TA, Iliadis LS et al (2009) Feature extraction for time-series data: An artificial neural network evolutionary training model for the management of mountainous watersheds. Neurocomputing 73:49–59. doi:10.1016/j.neucom.2008.08.024
-
(2009)
Neurocomputing
, vol.73
, pp. 49-59
-
-
Glezakos, T.J.1
Tsiligiridis, T.A.2
Iliadis, L.S.3
-
69
-
-
84899975429
-
Modeling of Sediment Yield Prediction Using M5 Model Tree Algorithm and Wavelet Regression
-
Goyal MK (2014) Modeling of Sediment Yield Prediction Using M5 Model Tree Algorithm and Wavelet Regression. Water Resour Manag 1991–2003. doi: 10.1007/s11269-014-0590-6
-
(2014)
Water Resour Manag
, pp. 1991-2003
-
-
Goyal, M.K.1
-
70
-
-
61849164592
-
Fuzzy prediction architecture using recurrent neural networks
-
Graves D, Pedrycz W (2009) Fuzzy prediction architecture using recurrent neural networks. Neurocomputing 72:1668–1678. doi:10.1016/j.neucom.2008.07.009
-
(2009)
Neurocomputing
, vol.72
, pp. 1668-1678
-
-
Graves, D.1
Pedrycz, W.2
-
71
-
-
0000562670
-
Decomposition of Hardy Function into Square Integrable Wavelets of Constant Shape
-
Grossmann A, Morlet J (1984) Decomposition of Hardy Function into Square Integrable Wavelets of Constant Shape. SIAM J Math Anal 15:723–736. doi:10.1137/0515056
-
(1984)
SIAM J Math Anal
, vol.15
, pp. 723-736
-
-
Grossmann, A.1
Morlet, J.2
-
72
-
-
0033372061
-
The classification of hydrologically homogeneous regions
-
Hall MJ, Minns AW (1999) The classification of hydrologically homogeneous regions. Hydrol Sci J 44:693–704. doi:10.1080/02626669909492268
-
(1999)
Hydrol Sci J
, vol.44
, pp. 693-704
-
-
Hall, M.J.1
Minns, A.W.2
-
73
-
-
3342965223
-
Prediction of wastewater treatment plant performance using artificial neural networks
-
Hamed MM, Khalafallah MG, Hassanien EA (2004) Prediction of wastewater treatment plant performance using artificial neural networks. Environ Model Softw 19:919–928. doi:10.1016/j.envsoft.2003.10.005
-
(2004)
Environ Model Softw
, vol.19
, pp. 919-928
-
-
Hamed, M.M.1
Khalafallah, M.G.2
Hassanien, E.A.3
-
74
-
-
84897363857
-
A comparative study of support vector machines and artificial neural networks for predicting precipitation in Iran
-
Hamidi O, Poorolajal J, Sadeghifar M (2014) A comparative study of support vector machines and artificial neural networks for predicting precipitation in Iran. Theor Appl Climatol. doi:10.1007/s00704-014-1141-z
-
(2014)
Theor Appl Climatol
-
-
Hamidi, O.1
Poorolajal, J.2
Sadeghifar, M.3
-
75
-
-
84867891849
-
A structure optimisation algorithm for feedforward neural network construction
-
Han H-G, Qiao J-F (2013) A structure optimisation algorithm for feedforward neural network construction. Neurocomputing 99:347–357. doi:10.1016/j.neucom.2012.07.023
-
(2013)
Neurocomputing
, vol.99
, pp. 347-357
-
-
Han, H.-G.1
Qiao, J.-F.2
-
76
-
-
0002370669
-
Reference crop evapotranspiration from temperature
-
Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1:96–99. doi:10.13031/2013.26773
-
(1985)
Appl Eng Agric
, vol.1
, pp. 96-99
-
-
Hargreaves, G.H.1
Samani, Z.A.2
-
77
-
-
84867099470
-
Dynamic nonlinear state-space model with a neural network via improved sequential learning algorithm for an online real-time hydrological modeling
-
Hong Y-ST (2012) Dynamic nonlinear state-space model with a neural network via improved sequential learning algorithm for an online real-time hydrological modeling. J Hydrol 468–469:11–21. doi:10.1016/j.jhydrol.2012.08.001
-
(2012)
J Hydrol
, vol.468-469
, pp. 11-21
-
-
Hong, Y.-S.T.1
-
78
-
-
17844365878
-
Self-organizing nonlinear output (SONO): a neural network suitable for cloud patch–based rainfall estimation at small scales
-
Hong Y, Hsu K, Sorooshian S, Gao X (2005) Self-organizing nonlinear output (SONO): a neural network suitable for cloud patch–based rainfall estimation at small scales. Water Resour Res 41. doi:10.1029/2004WR003142
-
(2005)
Water Resour Res
, pp. 41
-
-
Hong, Y.1
Hsu, K.2
Sorooshian, S.3
Gao, X.4
-
79
-
-
0024880831
-
Multilayer feedforward networks are universal approximators
-
Hornik K, Stinchcombe M, White H (1989) Multilayer feedforward networks are universal approximators. Neural Netw 2:359–366. doi:10.1016/0893-6080(89)90020-8
-
(1989)
Neural Netw
, vol.2
, pp. 359-366
-
-
Hornik, K.1
Stinchcombe, M.2
White, H.3
-
80
-
-
84878764686
-
Intelligent Systems in Optimizing Reservoir Operation Policy: A Review
-
Hossain MS, El-shafie A (2013) Intelligent Systems in Optimizing Reservoir Operation Policy: A Review. Water Resour Manag 27:3387–3407. doi:10.1007/s11269-013-0353-9
-
(2013)
Water Resour Manag
, vol.27
, pp. 3387-3407
-
-
Hossain, M.S.1
El-shafie, A.2
-
81
-
-
84893923942
-
Multilayer perceptron with different training algorithms for streamflow forecasting
-
Hosseinzadeh Talaee P (2014) Multilayer perceptron with different training algorithms for streamflow forecasting. Neural Comput Applic 24:695–703. doi:10.1007/s00521-012-1287-5
-
(2014)
Neural Comput Applic
, vol.24
, pp. 695-703
-
-
Hosseinzadeh Talaee, P.1
-
82
-
-
0036998831
-
Self-organizing linear output map (SOLO): An artificial neural network suitable for hydrologic modeling and analysis
-
Hsu K, Gupta HV, Gao X et al (2002) Self-organizing linear output map (SOLO): An artificial neural network suitable for hydrologic modeling and analysis. Water Resour Res 38:38-1. doi:10.1029/2001WR000795
-
(2002)
Water Resour Res
, vol.38
, pp. 31-38
-
-
Hsu, K.1
Gupta, H.V.2
Gao, X.3
-
83
-
-
17444385970
-
A Modified Neural Network for Improving River Flow Prediction/Un Réseau de Neurones Modifié pour Améliorer la Prévision de L’écoulement Fluvial
-
Hu TS, Lam KC, Ng ST (2005) A Modified Neural Network for Improving River Flow Prediction/Un Réseau de Neurones Modifié pour Améliorer la Prévision de L’écoulement Fluvial. Hydrolog Sci J 50:299–318. doi:10.1623/hysj.50.2.299.60649
-
(2005)
Hydrolog Sci J
, vol.50
, pp. 299-318
-
-
Hu, T.S.1
Lam, K.C.2
Ng, S.T.3
-
84
-
-
84856234248
-
Integrated neural networks for monthly river flow estimation in arid inland basin of Northwest China
-
Huo Z, Feng S, Kang S et al (2012) Integrated neural networks for monthly river flow estimation in arid inland basin of Northwest China. J Hydrol 420–421:159–170. doi:10.1016/j.jhydrol.2011.11.054
-
(2012)
J Hydrol
, vol.420-421
, pp. 159-170
-
-
Huo, Z.1
Feng, S.2
Kang, S.3
-
85
-
-
33846820421
-
An Artificial Neural Network model for mountainous water-resources management: The case of Cyprus mountainous watersheds
-
Iliadis LS, Maris F (2007) An Artificial Neural Network model for mountainous water-resources management: The case of Cyprus mountainous watersheds. Environ Model Softw 22:1066–1072. doi:10.1016/j.envsoft.2006.05.026
-
(2007)
Environ Model Softw
, vol.22
, pp. 1066-1072
-
-
Iliadis, L.S.1
Maris, F.2
-
86
-
-
84875520036
-
Modeling effects of changing land use/cover on daily streamflow: An Artificial Neural Network and curve number based hybrid approach
-
Isik S, Kalin L, Schoonover JE et al (2013) Modeling effects of changing land use/cover on daily streamflow: An Artificial Neural Network and curve number based hybrid approach. J Hydrol 485:103–112. doi:10.1016/j.jhydrol.2012.08.032
-
(2013)
J Hydrol
, vol.485
, pp. 103-112
-
-
Isik, S.1
Kalin, L.2
Schoonover, J.E.3
-
87
-
-
33846813334
-
Hybrid neural network models for hydrologic time series forecasting
-
Jain A, Kumar AM (2007) Hybrid neural network models for hydrologic time series forecasting. Appl Soft Comput J 7:585–592. doi:10.1016/j.asoc.2006.03.002
-
(2007)
Appl Soft Comput J
, vol.7
, pp. 585-592
-
-
Jain, A.1
Kumar, A.M.2
-
88
-
-
28844473522
-
Integrated approach to model decomposed flow hydrograph using artificial neural network and conceptual techniques
-
Jain A, Srinivasulu S (2006) Integrated approach to model decomposed flow hydrograph using artificial neural network and conceptual techniques. J Hydrol 317:291–306. doi:10.1016/j.jhydrol.2005.05.022
-
(2006)
J Hydrol
, vol.317
, pp. 291-306
-
-
Jain, A.1
Srinivasulu, S.2
-
89
-
-
70349765658
-
Combining single-value streamflow forecasts - A review and guidelines for selecting techniques
-
Jeong DI, Kim YO (2009) Combining single-value streamflow forecasts - A review and guidelines for selecting techniques. J Hydrol 377:284–299. doi:10.1016/j.jhydrol.2009.08.028
-
(2009)
J Hydrol
, vol.377
, pp. 284-299
-
-
Jeong, D.I.1
Kim, Y.O.2
-
90
-
-
33750682003
-
Bootstrapped artificial neural networks for synthetic flow generation with a small data sample
-
Jia Y, Culver TB (2006) Bootstrapped artificial neural networks for synthetic flow generation with a small data sample. J Hydrol 331:580–590. doi:10.1016/j.jhydrol.2006.06.005
-
(2006)
J Hydrol
, vol.331
, pp. 580-590
-
-
Jia, Y.1
Culver, T.B.2
-
91
-
-
84862673732
-
Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data
-
Jothiprakash V, Magar RB (2012) Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data. J Hydrol 450–451:293–307. doi:10.1016/j.jhydrol.2012.04.045
-
(2012)
J Hydrol
, vol.450-451
, pp. 293-307
-
-
Jothiprakash, V.1
Magar, R.B.2
-
92
-
-
72449178709
-
Division-based rainfall-runoff simulations with BP neural networks and Xinanjiang model
-
Ju Q, Yu Z, Hao Z et al (2009) Division-based rainfall-runoff simulations with BP neural networks and Xinanjiang model. Neurocomputing 72:2873–2883. doi:10.1016/j.neucom.2008.12.032
-
(2009)
Neurocomputing
, vol.72
, pp. 2873-2883
-
-
Ju, Q.1
Yu, Z.2
Hao, Z.3
-
93
-
-
77957016230
-
Application of radial basis function neural networks to short-term streamflow forecasting
-
Kagoda PA, Ndiritu J, Ntuli C, Mwaka B (2010) Application of radial basis function neural networks to short-term streamflow forecasting. Phys Chem Earth 35:571–581. doi:10.1016/j.pce.2010.07.021
-
(2010)
Phys Chem Earth
, vol.35
, pp. 571-581
-
-
Kagoda, P.A.1
Ndiritu, J.2
Ntuli, C.3
Mwaka, B.4
-
94
-
-
34147214608
-
Interpolating monthly precipitation by self-organizing map (SOM) and multilayer perceptron (MLP)
-
Kalteh AM, Berndtsson R (2007) Interpolating monthly precipitation by self-organizing map (SOM) and multilayer perceptron (MLP). Hydrol Sci J 52:305–317. doi:10.1623/hysj.52.2.305
-
(2007)
Hydrol Sci J
, vol.52
, pp. 305-317
-
-
Kalteh, A.M.1
Berndtsson, R.2
-
95
-
-
40749144865
-
Review of the self-organizing map (SOM) approach in water resources: Analysis, modelling and application
-
Kalteh AM, Hjorth P, Berndtsson R (2008) Review of the self-organizing map (SOM) approach in water resources: Analysis, modelling and application. Environ Model Softw 23:835–845. doi:10.1016/j.envsoft.2007.10.001
-
(2008)
Environ Model Softw
, vol.23
, pp. 835-845
-
-
Kalteh, A.M.1
Hjorth, P.2
Berndtsson, R.3
-
97
-
-
33646572227
-
Chaotic time series prediction with a global model: artificial neural network
-
Karunasinghe DSK, Liong S-Y (2006) Chaotic time series prediction with a global model: artificial neural network. J Hydrol 323:92–105. doi:10.1016/j.jhydrol.2005.07.048
-
(2006)
J Hydrol
, vol.323
, pp. 92-105
-
-
Karunasinghe, D.S.K.1
Liong, S.-Y.2
-
98
-
-
84881236620
-
Constructing prediction interval for artificial neural network rainfall runoff models based on ensemble simulations
-
Kasiviswanathan KS, Cibin R, Sudheer KP, Chaubey I (2013) Constructing prediction interval for artificial neural network rainfall runoff models based on ensemble simulations. J Hydrol 499:275–288. doi:10.1016/j.jhydrol.2013.06.043
-
(2013)
J Hydrol
, vol.499
, pp. 275-288
-
-
Kasiviswanathan, K.S.1
Cibin, R.2
Sudheer, K.P.3
Chaubey, I.4
-
99
-
-
62349132975
-
Increasing the accuracy of neural network classification using refined training data
-
Kavzoglu T (2009) Increasing the accuracy of neural network classification using refined training data. Environ Model Softw 24:850–858. doi:10.1016/j.envsoft.2008.11.012
-
(2009)
Environ Model Softw
, vol.24
, pp. 850-858
-
-
Kavzoglu, T.1
-
100
-
-
69349098138
-
Estimation of river flow by artificial neural networks and identification of input vectors susceptible to producing unreliable flow estimates
-
Kentel E (2009) Estimation of river flow by artificial neural networks and identification of input vectors susceptible to producing unreliable flow estimates. J Hydrol 375:481–488. doi:10.1016/j.jhydrol.2009.06.051
-
(2009)
J Hydrol
, vol.375
, pp. 481-488
-
-
Kentel, E.1
-
101
-
-
28944434082
-
Methods to improve the neural network performance in suspended sediment estimation
-
Kerem Cigizoglu H, Kisi Ö̈ (2006) Methods to improve the neural network performance in suspended sediment estimation. J Hydrol 317:221–238. doi:10.1016/j.jhydrol.2005.05.019
-
(2006)
J Hydrol
, vol.317
, pp. 221-238
-
-
Kerem Cigizoglu, H.1
Kisi, Ö.2
-
102
-
-
31444439227
-
Artificial neural network models of daily pan evaporation
-
Keskin ME, Terzi Ö (2006) Artificial neural network models of daily pan evaporation. J Hydrol Eng 11:65–70. doi:10.1061/(ASCE)1084-0699(2006)11:1(65)
-
(2006)
J Hydrol Eng
, vol.11
, pp. 65-70
-
-
Keskin, M.E.1
Terzi, Ö.2
-
103
-
-
78651464522
-
Modified particle swarm optimization for probabilistic slope stability analysis
-
Khajehzadeh M, El-Shafie A, Raihan T (2010) Modified particle swarm optimization for probabilistic slope stability analysis. Int J Phys Sci 5:2248–2258
-
(2010)
Int J Phys Sci
, vol.5
, pp. 2248-2258
-
-
Khajehzadeh, M.1
El-Shafie, A.2
Raihan, T.3
-
105
-
-
0035977694
-
Groups and neural networks based streamflow data infilling procedures
-
Khalil M, Panu U, Lennox W (2001) Groups and neural networks based streamflow data infilling procedures. J Hydrol 241:153–176. doi:10.1016/S0022-1694(00)00332-2
-
(2001)
J Hydrol
, vol.241
, pp. 153-176
-
-
Khalil, M.1
Panu, U.2
Lennox, W.3
-
106
-
-
70349453596
-
An artificial neural network (p, d, q) model for timeseries forecasting
-
Khashei M, Bijari M (2010) An artificial neural network (p, d, q) model for timeseries forecasting. Expert Syst Appl 37:479–489. doi:10.1016/j.eswa.2009.05.044
-
(2010)
Expert Syst Appl
, vol.37
, pp. 479-489
-
-
Khashei, M.1
Bijari, M.2
-
107
-
-
79956352538
-
Comparison of three artificial intelligence techniques for discharge routing
-
Khatibi R, Ghorbani MA, Kashani MH, Kisi O (2011) Comparison of three artificial intelligence techniques for discharge routing. J Hydrol 403:201–212. doi:10.1016/j.jhydrol.2011.03.007
-
(2011)
J Hydrol
, vol.403
, pp. 201-212
-
-
Khatibi, R.1
Ghorbani, M.A.2
Kashani, M.H.3
Kisi, O.4
-
108
-
-
84929323011
-
Model for prediction of evapotranspiration using MLP neural network
-
Khoshhal J, Mokarram M (2012) Model for prediction of evapotranspiration using MLP neural network. Int J Environ Sci 3:1000–1009. doi:10.6088/ijes.2012030133008
-
(2012)
Int J Environ Sci
, vol.3
, pp. 1000-1009
-
-
Khoshhal, J.1
Mokarram, M.2
-
109
-
-
0035370678
-
Quantitative flood forecasting using multisensor data and neural networks
-
Kim G, Barros AP (2001) Quantitative flood forecasting using multisensor data and neural networks. J Hydrol 246:45–62. doi:10.1016/j.jhydrol.2010.09.005
-
(2001)
J Hydrol
, vol.246
, pp. 45-62
-
-
Kim, G.1
Barros, A.P.2
-
110
-
-
39849084753
-
Neural networks and genetic algorithm approach for nonlinear evaporation and evapotranspiration modeling
-
Kim S, Kim HS (2008) Neural networks and genetic algorithm approach for nonlinear evaporation and evapotranspiration modeling. J Hydrol 351:299–317. doi:10.1016/j.jhydrol.2007.12.014
-
(2008)
J Hydrol
, vol.351
, pp. 299-317
-
-
Kim, S.1
Kim, H.S.2
-
111
-
-
78149406829
-
Reconstructing missing daily precipitation data using regression trees and artificial neural networks for SWAT streamflow simulation
-
Kim JW, Pachepsky YA (2010) Reconstructing missing daily precipitation data using regression trees and artificial neural networks for SWAT streamflow simulation. J Hydrol 394:305–314. doi:10.1016/j.jhydrol.2010.09.005
-
(2010)
J Hydrol
, vol.394
, pp. 305-314
-
-
Kim, J.W.1
Pachepsky, Y.A.2
-
112
-
-
28444444200
-
Calibration and validation of neural networks to ensure physically plausible hydrological modeling
-
Kingston GB, Maier HR, Lambert MF (2005) Calibration and validation of neural networks to ensure physically plausible hydrological modeling. J Hydrol 314:158–176. doi:10.1016/j.jhydrol.2005.03.013
-
(2005)
J Hydrol
, vol.314
, pp. 158-176
-
-
Kingston, G.B.1
Maier, H.R.2
Lambert, M.F.3
-
113
-
-
23044459648
-
Suspended sediment estimation using neuro-fuzzy and neural network approaches
-
Kisi O (2005) Suspended sediment estimation using neuro-fuzzy and neural network approaches. Hydrol Sci J 50:683–696. doi:10.1623/hysj.2005.50.4.683
-
(2005)
Hydrol Sci J
, vol.50
, pp. 683-696
-
-
Kisi, O.1
-
114
-
-
33845321370
-
Generalized regression neural networks for evapotranspiration modelling
-
Kisi Ö (2006) Generalized regression neural networks for evapotranspiration modelling. Hydrol Sci J 51:1092–1105
-
(2006)
Hydrol Sci J
, vol.51
, pp. 1092-1105
-
-
Kisi, Ö.1
-
115
-
-
48649099727
-
The potential of different ANN techniques in evapotranspiration modelling
-
Kisi O (2008) The potential of different ANN techniques in evapotranspiration modelling. Hydrol Process 22:2449–2460. doi:10.1002/hyp.6837
-
(2008)
Hydrol Process
, vol.22
, pp. 2449-2460
-
-
Kisi, O.1
-
116
-
-
77955049922
-
Wavelet regression model for short-term streamflow forecasting
-
Kisi O (2010) Wavelet regression model for short-term streamflow forecasting. J Hydrol 389:344–353. doi:10.1016/j.jhydrol.2010.06.013
-
(2010)
J Hydrol
, vol.389
, pp. 344-353
-
-
Kisi, O.1
-
117
-
-
77954384995
-
River suspended sediment concentration modeling using a neural differential evolution approach
-
Kişi Ö (2010) River suspended sediment concentration modeling using a neural differential evolution approach. J Hydrol 389:227–235. doi:10.1016/j.jhydrol.2010.06.003
-
(2010)
J Hydrol
, vol.389
, pp. 227-235
-
-
Kişi, Ö.1
-
118
-
-
84880140052
-
Evolutionary neural networks for monthly pan evaporation modeling
-
Kişi Ö (2013) Evolutionary neural networks for monthly pan evaporation modeling. J Hydrol 498:36–45. doi:10.1016/j.jhydrol.2013.06.011
-
(2013)
J Hydrol
, vol.498
, pp. 36-45
-
-
Kişi, Ö.1
-
119
-
-
34548425056
-
Comparison of different ANN techniques in river flow prediction
-
Kisi O, Cigizoglu HK (2007) Comparison of different ANN techniques in river flow prediction. Civ Eng Environ Syst 24:211–231. doi:10.1080/10286600600888565
-
(2007)
Civ Eng Environ Syst
, vol.24
, pp. 211-231
-
-
Kisi, O.1
Cigizoglu, H.K.2
-
120
-
-
34547116654
-
Adaptive neurofuzzy computing technique for evapotranspiration estimation
-
Kisi Ö, Ozturk O (2007) Adaptive neurofuzzy computing technique for evapotranspiration estimation. J Irrig Drain Eng 133:368–379
-
(2007)
J Irrig Drain Eng
, vol.133
, pp. 368-379
-
-
Kisi, Ö.1
Ozturk, O.2
-
121
-
-
57049168146
-
Modelling daily suspended sediment of rivers in Turkey using several data-driven techniques / Modélisation de la charge journalière en matières en suspension dans des rivières turques à l’aide de plusieurs techniques empiriques
-
Kisi O, Yuksel I, Dogan E (2008) Modelling daily suspended sediment of rivers in Turkey using several data-driven techniques / Modélisation de la charge journalière en matières en suspension dans des rivières turques à l’aide de plusieurs techniques empiriques. Hydrol Sci J 53:1270–1285. doi:10.1623/hysj.53.6.1270
-
(2008)
Hydrol Sci J
, vol.53
, pp. 1270-1285
-
-
Kisi, O.1
Yuksel, I.2
Dogan, E.3
-
122
-
-
84857912130
-
Forecasting daily lake levels using artificial intelligence approaches
-
Kisi O, Shiri J, Nikoofar B (2012) Forecasting daily lake levels using artificial intelligence approaches. Comput Geosci 41:169–180. doi:10.1016/j.cageo.2011.08.027
-
(2012)
Comput Geosci
, vol.41
, pp. 169-180
-
-
Kisi, O.1
Shiri, J.2
Nikoofar, B.3
-
123
-
-
84870159777
-
Modeling rainfall-runoff process using soft computing techniques
-
Kisi O, Shiri J, Tombul M (2013) Modeling rainfall-runoff process using soft computing techniques. Comput Geosci 51:108–117. doi:10.1016/j.cageo.2012.07.001
-
(2013)
Comput Geosci
, vol.51
, pp. 108-117
-
-
Kisi, O.1
Shiri, J.2
Tombul, M.3
-
124
-
-
0141648644
-
A neural network approach for the optimisation of watershed management
-
Kralisch S, Fink M, Flügel W-A, Beckstein C (2003) A neural network approach for the optimisation of watershed management. Environ Model Softw 18:815–823. doi:10.1016/S1364-8152(03)00081-1
-
(2003)
Environ Model Softw
, vol.18
, pp. 815-823
-
-
Kralisch, S.1
Fink, M.2
Flügel, W.-A.3
Beckstein, C.4
-
125
-
-
0036635791
-
Estimating evapotranspiration using artificial neural network
-
Kumar M, Raghuwanshi N, Singh R et al (2002) Estimating evapotranspiration using artificial neural network. J Irrig Drain Eng 128:224–233. doi:10.1061/(ASCE)0733-9437(2002)128:4(224)
-
(2002)
J Irrig Drain Eng
, vol.128
, pp. 224-233
-
-
Kumar, M.1
Raghuwanshi, N.2
Singh, R.3
-
126
-
-
77958490131
-
Seasonal streamflow prediction by a combined climate-hydrologic system for river basins of Taiwan
-
Kuo CC, Gan TY, Yu PS (2010) Seasonal streamflow prediction by a combined climate-hydrologic system for river basins of Taiwan. J Hydrol 387:292–303. doi:10.1016/j.jhydrol.2010.04.020
-
(2010)
J Hydrol
, vol.387
, pp. 292-303
-
-
Kuo, C.C.1
Gan, T.Y.2
Yu, P.S.3
-
127
-
-
42049121124
-
Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (Northern Spain)
-
Landeras G, Ortiz-Barredo A, López JJ (2008) Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (Northern Spain). Agric Water Manag 95:553–565. doi:10.1016/j.agwat.2007.12.011
-
(2008)
Agric Water Manag
, vol.95
, pp. 553-565
-
-
Landeras, G.1
Ortiz-Barredo, A.2
López, J.J.3
-
128
-
-
43949087486
-
Structural optimisation and input selection of an artificial neural network for river level prediction
-
Leahy P, Kiely G, Corcoran G (2008) Structural optimisation and input selection of an artificial neural network for river level prediction. J Hydrol 355:192–201. doi:10.1016/j.jhydrol.2008.03.017
-
(2008)
J Hydrol
, vol.355
, pp. 192-201
-
-
Leahy, P.1
Kiely, G.2
Corcoran, G.3
-
129
-
-
33646564705
-
Identification of homogeneous regions for regional frequency analysis using the self-organizing map
-
Lin GF, Chen LH (2006) Identification of homogeneous regions for regional frequency analysis using the self-organizing map. J Hydrol 324:1–9. doi:10.1016/j.jhydrol.2005.09.009
-
(2006)
J Hydrol
, vol.324
, pp. 1-9
-
-
Lin, G.F.1
Chen, L.H.2
-
130
-
-
69349084510
-
A hybrid neural network model for typhoon-rainfall forecasting
-
Lin G-F, Wu M-C (2009) A hybrid neural network model for typhoon-rainfall forecasting. J Hydrol 375:450–458. doi:10.1016/j.jhydrol.2009.06.047
-
(2009)
J Hydrol
, vol.375
, pp. 450-458
-
-
Lin, G.-F.1
Wu, M.-C.2
-
131
-
-
38949116337
-
Predicting faecal indicator levels in estuarine receiving waters—an integrated hydrodynamic and ANN modelling approach
-
Lin B, Syed M, Falconer RA (2008) Predicting faecal indicator levels in estuarine receiving waters—an integrated hydrodynamic and ANN modelling approach. Environ Model Softw 23:729–740. doi:10.1016/j.envsoft.2007.09.009
-
(2008)
Environ Model Softw
, vol.23
, pp. 729-740
-
-
Lin, B.1
Syed, M.2
Falconer, R.A.3
-
133
-
-
84873742567
-
Modeling the daily suspended sediment concentration in a hyperconcentrated river on the Loess Plateau, China, using the Wavelet-ANN approach
-
Liu QJ, Shi ZH, Fang NF et al (2013) Modeling the daily suspended sediment concentration in a hyperconcentrated river on the Loess Plateau, China, using the Wavelet-ANN approach. Geomorphology 186:181–190. doi:10.1016/j.geomorph.2013.01.012
-
(2013)
Geomorphology
, vol.186
, pp. 181-190
-
-
Liu, Q.J.1
Shi, Z.H.2
Fang, N.F.3
-
134
-
-
75149198666
-
Formal verification of wastewater treatment processes using events detected from continuous signals by means of artificial neural networks. Case study: SBR plant
-
Luccarini L, Bragadin GL, Colombini G et al (2010) Formal verification of wastewater treatment processes using events detected from continuous signals by means of artificial neural networks. Case study: SBR plant. Environ Model Softw 25:648–660. doi:10.1016/j.envsoft.2009.05.013
-
(2010)
Environ Model Softw
, vol.25
, pp. 648-660
-
-
Luccarini, L.1
Bragadin, G.L.2
Colombini, G.3
-
135
-
-
84862648048
-
Wavelet-Volterra coupled model for monthly stream flow forecasting
-
Maheswaran R, Khosa R (2012a) Wavelet-Volterra coupled model for monthly stream flow forecasting. J Hydrol 450–451:320–335. doi:10.1016/j.jhydrol.2012.04.017
-
(2012)
J Hydrol
, vol.450-451
, pp. 320-335
-
-
Maheswaran, R.1
Khosa, R.2
-
136
-
-
84862642100
-
Comparative study of different wavelets for hydrologic forecasting
-
Maheswaran R, Khosa R (2012b) Comparative study of different wavelets for hydrologic forecasting. Comput Geosci 46:284–295. doi:10.1016/j.cageo.2011.12.015
-
(2012)
Comput Geosci
, vol.46
, pp. 284-295
-
-
Maheswaran, R.1
Khosa, R.2
-
137
-
-
0032034197
-
Understanding the behaviour and optimising the performance of back-propagation neural networks: An empirical study
-
Maier HR, Dandy GC (1998) Understanding the behaviour and optimising the performance of back-propagation neural networks: An empirical study. Environ Model Softw 13:179–191. doi:10.1016/S1364-8152(98)00019-X
-
(1998)
Environ Model Softw
, vol.13
, pp. 179-191
-
-
Maier, H.R.1
Dandy, G.C.2
-
138
-
-
0033957764
-
Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications
-
Maier HR, Dandy GC (2000) Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications. Environ Model Softw 15:101–124. doi:10.1016/S1364-8152(99)00007-9
-
(2000)
Environ Model Softw
, vol.15
, pp. 101-124
-
-
Maier, H.R.1
Dandy, G.C.2
-
139
-
-
0035108726
-
Neural network based modelling of environmental variables: a systematic approach
-
Maier HR, Dandy GC (2001) Neural network based modelling of environmental variables: a systematic approach. Math Comput Model 33:669–682. doi:10.1016/S0895-7177(00)00271-5
-
(2001)
Math Comput Model
, vol.33
, pp. 669-682
-
-
Maier, H.R.1
Dandy, G.C.2
-
140
-
-
1642336479
-
Use of artificial neural networks for predicting optimal alum doses and treated water quality parameters
-
Maier HR, Morgan N, Chow CWK (2004) Use of artificial neural networks for predicting optimal alum doses and treated water quality parameters. Environ Model Softw 19:485–494. doi:10.1016/S1364-8152(03)00163-4
-
(2004)
Environ Model Softw
, vol.19
, pp. 485-494
-
-
Maier, H.R.1
Morgan, N.2
Chow, C.W.K.3
-
141
-
-
77951175284
-
Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions
-
Maier HR, Jain A, Dandy GC, Sudheer KP (2010) Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions. Environ Model Softw 25:891–909. doi:10.1016/j.envsoft.2010.02.003
-
(2010)
Environ Model Softw
, vol.25
, pp. 891-909
-
-
Maier, H.R.1
Jain, A.2
Dandy, G.C.3
Sudheer, K.P.4
-
142
-
-
53149113747
-
Prediction of urban stormwater quality using artificial neural networks
-
May DB, Sivakumar M (2009) Prediction of urban stormwater quality using artificial neural networks. Environ Model Softw 24:296–302. doi:10.1016/j.envsoft.2008.07.004
-
(2009)
Environ Model Softw
, vol.24
, pp. 296-302
-
-
May, D.B.1
Sivakumar, M.2
-
143
-
-
44749087176
-
Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems
-
May RJ, Dandy GC, Maier HR, Nixon JB (2008a) Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems. Environ Model Softw 23:1289–1299. doi:10.1016/j.envsoft.2008.03.008
-
(2008)
Environ Model Softw
, vol.23
, pp. 1289-1299
-
-
May, R.J.1
Dandy, G.C.2
Maier, H.R.3
Nixon, J.B.4
-
144
-
-
44749087316
-
Non-linear variable selection for artificial neural networks using partial mutual information
-
May RJ, Maier HR, Dandy GC, Fernando TMKG (2008b) Non-linear variable selection for artificial neural networks using partial mutual information. Environ Model Softw 23:1312–1326. doi:10.1016/j.envsoft.2008.03.007
-
(2008)
Environ Model Softw
, vol.23
, pp. 1312-1326
-
-
May, R.J.1
Maier, H.R.2
Dandy, G.C.3
Fernando, T.M.K.G.4
-
145
-
-
51249194645
-
A logical calculus of the ideas immanent in nervous activity
-
McCulloch WS, Pitts W (1943) A logical calculus of the ideas immanent in nervous activity. Bull Math Biophys 5:115–133. doi:10.1007/BF02478259
-
(1943)
Bull Math Biophys
, vol.5
, pp. 115-133
-
-
McCulloch, W.S.1
Pitts, W.2
-
146
-
-
0030159380
-
Artificial neural networks as rainfall- runoff models
-
Minns AW, Hall MJ (1996) Artificial neural networks as rainfall- runoff models. Hydrol Sci J 41:399–418. doi:10.1080/02626669609491511
-
(1996)
Hydrol Sci J
, vol.41
, pp. 399-418
-
-
Minns, A.W.1
Hall, M.J.2
-
147
-
-
57549095413
-
Evaporation estimation using artificial neural networks and adaptive neuro-fuzzy inference system techniques
-
Moghaddamnia A, Ghafari Gousheh M, Piri J et al (2009) Evaporation estimation using artificial neural networks and adaptive neuro-fuzzy inference system techniques. Adv Water Resour 32:88–97. doi:10.1016/j.advwatres.2008.10.005
-
(2009)
Adv Water Resour
, vol.32
, pp. 88-97
-
-
Moghaddamnia, A.1
Ghafari Gousheh, M.2
Piri, J.3
-
148
-
-
3142538909
-
Improved streamflow forecasting using self-organizing radial basis function artificial neural networks
-
Moradkhani H, Hsu K, Gupta HV, Sorooshian S (2004) Improved streamflow forecasting using self-organizing radial basis function artificial neural networks. J Hydrol 295:246–262. doi:10.1016/j.jhydrol.2004.03.027
-
(2004)
J Hydrol
, vol.295
, pp. 246-262
-
-
Moradkhani, H.1
Hsu, K.2
Gupta, H.V.3
Sorooshian, S.4
-
149
-
-
0027816556
-
Kitamura S (1993) A Hybrid Neural Network System for the Rainfall Estimation using Satellite Imagery
-
International Joint Conference on Neural Networks, Nagoya
-
Murao H, Nishikawa I, Kitamura S (1993) A Hybrid Neural Network System for the Rainfall Estimation using Satellite Imagery. In: Proc. IJCNN-93, International Joint Conference on Neural Networks, Nagoya. pp 1211–1214
-
Proc. IJCNN-93
, pp. 1211-1214
-
-
Murao, H.1
Nishikawa, I.2
-
150
-
-
84860486004
-
River suspended sediment prediction using various multilayer perceptron neural network training algorithm—a case study in Malaysia
-
Mustafa MR, Rezaur RB, Saiedi S, Isa MH (2012) River suspended sediment prediction using various multilayer perceptron neural network training algorithm—a case study in Malaysia. Water Resour Manag 26:1879–1897. doi:10.1007/s11269-012-9992-5
-
(2012)
Water Resour Manag
, vol.26
, pp. 1879-1897
-
-
Mustafa, M.R.1
Rezaur, R.B.2
Saiedi, S.3
Isa, M.H.4
-
151
-
-
67650293317
-
Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed
-
Mutlu E, Chaubey I, Hexmoor H, Bajwa SG (2008) Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed. Hydrol Process 22:5097–5106. doi:10.1002/hyp.7136
-
(2008)
Hydrol Process
, vol.22
, pp. 5097-5106
-
-
Mutlu, E.1
Chaubey, I.2
Hexmoor, H.3
Bajwa, S.G.4
-
152
-
-
65249087289
-
Prediction of Johor River water quality parameters using artificial neural networks
-
Najah A, Elshafie A, Karim OA, Jaffar O (2009) Prediction of Johor River water quality parameters using artificial neural networks. Eur J Sci Res 28:422–435
-
(2009)
Eur J Sci Res
, vol.28
, pp. 422-435
-
-
Najah, A.1
Elshafie, A.2
Karim, O.A.3
Jaffar, O.4
-
153
-
-
80052193257
-
Integrated versus isolated scenario for prediction dissolved oxygen at progression of water quality monitoring stations
-
Najah A, El-Shafie A, Karim OA, Jaafar O (2011) Integrated versus isolated scenario for prediction dissolved oxygen at progression of water quality monitoring stations. Hydrol Earth Syst Sci 15:2693–2708. doi:10.5194/hess-15-2693-2011
-
(2011)
Hydrol Earth Syst Sci
, vol.15
, pp. 2693-2708
-
-
Najah, A.1
El-Shafie, A.2
Karim, O.A.3
Jaafar, O.4
-
154
-
-
77953022240
-
A conceptual and neural network model for real-time flood forecasting of the Tiber River in Rome
-
Napolitano G, See L, Calvo B et al (2010) A conceptual and neural network model for real-time flood forecasting of the Tiber River in Rome. Phys Chem Earth A B C 35:187–194. doi:10.1016/j.pce.2009.12.004
-
(2010)
Phys Chem Earth A B C
, vol.35
, pp. 187-194
-
-
Napolitano, G.1
See, L.2
Calvo, B.3
-
155
-
-
84877830096
-
Rainfall-runoff modeling using conceptual, data driven, and wavelet based computing approach
-
Nayak PC, Venkatesh B, Krishna B, Jain SK (2013) Rainfall-runoff modeling using conceptual, data driven, and wavelet based computing approach. J Hydrol 493:57–67. doi:10.1016/j.jhydrol.2013.04.016
-
(2013)
J Hydrol
, vol.493
, pp. 57-67
-
-
Nayak, P.C.1
Venkatesh, B.2
Krishna, B.3
Jain, S.K.4
-
156
-
-
33645973241
-
Monthly runoff simulation: comparing and combining conceptual and neural network models
-
Nilsson P, Uvo CB, Berndtsson R (2006) Monthly runoff simulation: comparing and combining conceptual and neural network models. J Hydrol 321:344–363. doi:10.1016/j.jhydrol.2005.08.007
-
(2006)
J Hydrol
, vol.321
, pp. 344-363
-
-
Nilsson, P.1
Uvo, C.B.2
Berndtsson, R.3
-
157
-
-
84876822959
-
A geomorphology-based ANFIS model for multi-station modeling of rainfall-runoff process
-
Nourani V, Komasi M (2013) A geomorphology-based ANFIS model for multi-station modeling of rainfall-runoff process. J Hydrol 490:41–55. doi:10.1016/j.jhydrol.2013.03.024
-
(2013)
J Hydrol
, vol.490
, pp. 41-55
-
-
Nourani, V.1
Komasi, M.2
-
158
-
-
79955025170
-
Two hybrid Artificial Intelligence approaches for modeling rainfall-runoff process
-
Nourani V, Kisi Ö, Komasi M (2011) Two hybrid Artificial Intelligence approaches for modeling rainfall-runoff process. J Hydrol 402:41–59. doi:10.1016/j.jhydrol.2011.03.002
-
(2011)
J Hydrol
, vol.402
, pp. 41-59
-
-
Nourani, V.1
Kisi, Ö.2
Komasi, M.3
-
159
-
-
84871025948
-
Using self-organizing maps and wavelet transforms for space-time pre-processing of satellite precipitation and runoff data in neural network based rainfall-runoff modeling
-
Nourani V, Baghanam AH, Adamowski J, Gebremichael M (2013) Using self-organizing maps and wavelet transforms for space-time pre-processing of satellite precipitation and runoff data in neural network based rainfall-runoff modeling. J Hydrol 476:228–243. doi:10.1016/j.jhydrol.2012.10.054
-
(2013)
J Hydrol
, vol.476
, pp. 228-243
-
-
Nourani, V.1
Baghanam, A.H.2
Adamowski, J.3
Gebremichael, M.4
-
160
-
-
84900481738
-
Applications of hybrid wavelet–Artificial Intelligence models in hydrology: a review
-
Nourani V, Hosseini Baghanam A, Adamowski J, Kisi O (2014) Applications of hybrid wavelet–Artificial Intelligence models in hydrology: a review. J Hydrol 514:358–377. doi:10.1016/j.jhydrol.2014.03.057
-
(2014)
J Hydrol
, vol.514
, pp. 358-377
-
-
Nourani, V.1
Hosseini Baghanam, A.2
Adamowski, J.3
Kisi, O.4
-
161
-
-
84865774272
-
A data-driven approach to predict suspended-sediment reference concentration under non-breaking waves
-
Oehler F, Coco G, Green MO, Bryan KR (2012) A data-driven approach to predict suspended-sediment reference concentration under non-breaking waves. Cont Shelf Res 46:96–106. doi:10.1016/j.csr.2011.01.015
-
(2012)
Cont Shelf Res
, vol.46
, pp. 96-106
-
-
Oehler, F.1
Coco, G.2
Green, M.O.3
Bryan, K.R.4
-
162
-
-
34548215689
-
IG-based genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons
-
Oh SK, Roh SB, Pedrycz W, Ahn TC (2007) IG-based genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons. Neurocomputing 70:2783–2798. doi:10.1016/j.neucom.2006.10.151
-
(2007)
Neurocomputing
, vol.70
, pp. 2783-2798
-
-
Oh, S.K.1
Roh, S.B.2
Pedrycz, W.3
Ahn, T.C.4
-
163
-
-
77950516820
-
A hybrid neural network and ARIMA model for water quality time series prediction
-
Ömer Faruk D (2010) A hybrid neural network and ARIMA model for water quality time series prediction. Eng Appl Artif Intell 23:586–594. doi:10.1016/j.engappai.2009.09.015
-
(2010)
Eng Appl Artif Intell
, vol.23
, pp. 586-594
-
-
Ömer Faruk, D.1
-
164
-
-
15944400056
-
Determination of the relationship between sewage odour and BOD by neural networks
-
Onkal-Engin G, Demir I, Engin SN (2005) Determination of the relationship between sewage odour and BOD by neural networks. Environ Model Softw 20:843–850. doi:10.1016/j.envsoft.2004.04.012
-
(2005)
Environ Model Softw
, vol.20
, pp. 843-850
-
-
Onkal-Engin, G.1
Demir, I.2
Engin, S.N.3
-
165
-
-
3242769911
-
State space neural networks for short term rainfall-runoff forecasting
-
Pan T, Wang R (2004) State space neural networks for short term rainfall-runoff forecasting. J Hydrol 297:34–50. doi:10.1016/j.jhydrol.2004.04.010
-
(2004)
J Hydrol
, vol.297
, pp. 34-50
-
-
Pan, T.1
Wang, R.2
-
166
-
-
48649085521
-
Estimation and forecasting of daily suspended sediment data using wavelet-neural networks
-
Partal T, Cigizoglu HK (2008) Estimation and forecasting of daily suspended sediment data using wavelet-neural networks. J Hydrol 358:317–331. doi:10.1016/j.jhydrol.2008.06.013
-
(2008)
J Hydrol
, vol.358
, pp. 317-331
-
-
Partal, T.1
Cigizoglu, H.K.2
-
167
-
-
84881499389
-
ANN hybrid model versus ARIMA and ARIMAX models of runoff coefficient
-
Pektaş AO, Kerem Cigizoglu H (2013) ANN hybrid model versus ARIMA and ARIMAX models of runoff coefficient. J Hydrol 500:21–36. doi:10.1016/j.jhydrol.2013.07.020
-
(2013)
J Hydrol
, vol.500
, pp. 21-36
-
-
Pektaş, A.O.1
Kerem Cigizoglu, H.2
-
168
-
-
84957790817
-
Natural evaporation from open water, bare soil and grass
-
Penman HL (1948) Natural evaporation from open water, bare soil and grass. Proc R Soc London Ser A Math Phys Sci 193:120–145. doi:10.1098/rspa.1948.0037
-
(1948)
Proc R Soc London Ser A Math Phys Sci
, vol.193
, pp. 120-145
-
-
Penman, H.L.1
-
169
-
-
80052028861
-
Optimizing neural networks for river flow forecasting - Evolutionary Computation methods versus the Levenberg-Marquardt approach
-
Piotrowski AP, Napiorkowski JJ (2011) Optimizing neural networks for river flow forecasting - Evolutionary Computation methods versus the Levenberg-Marquardt approach. J Hydrol 407:12–27. doi:10.1016/j.jhydrol.2011.06.019
-
(2011)
J Hydrol
, vol.407
, pp. 12-27
-
-
Piotrowski, A.P.1
Napiorkowski, J.J.2
-
170
-
-
84871010255
-
A comparison of methods to avoid overfitting in neural networks training in the case of catchment runoff modelling
-
Piotrowski AP, Napiorkowski JJ (2013) A comparison of methods to avoid overfitting in neural networks training in the case of catchment runoff modelling. J Hydrol 476:97–111. doi:10.1016/j.jhydrol.2012.10.019
-
(2013)
J Hydrol
, vol.476
, pp. 97-111
-
-
Piotrowski, A.P.1
Napiorkowski, J.J.2
-
171
-
-
59049088362
-
Improved irrigation water demand forecasting using a soft-computing hybrid model
-
Pulido-Calvo I, Gutiérrez-Estrada JC (2009) Improved irrigation water demand forecasting using a soft-computing hybrid model. Biosyst Eng 102:202–218. doi:10.1016/j.biosystemseng.2008.09.032
-
(2009)
Biosyst Eng
, vol.102
, pp. 202-218
-
-
Pulido-Calvo, I.1
Gutiérrez-Estrada, J.C.2
-
172
-
-
33845620661
-
Application of neural approaches to one-step daily flow forecasting in Portuguese watersheds
-
Pulido-Calvo I, Portela MM (2007) Application of neural approaches to one-step daily flow forecasting in Portuguese watersheds. J Hydrol 332:1–15. doi:10.1016/j.jhydrol.2006.06.015
-
(2007)
J Hydrol
, vol.332
, pp. 1-15
-
-
Pulido-Calvo, I.1
Portela, M.M.2
-
173
-
-
38649139150
-
A self-organizing fuzzy neural network and its applications to function approximation and forecast modeling
-
Qiao J, Wang H (2008) A self-organizing fuzzy neural network and its applications to function approximation and forecast modeling. Neurocomputing 71:564–569. doi:10.1016/j.neucom.2007.07.026
-
(2008)
Neurocomputing
, vol.71
, pp. 564-569
-
-
Qiao, J.1
Wang, H.2
-
174
-
-
31444443313
-
Runoff and Sediment Yield Modeling Using Artificial Neural Networks: Upper Siwane River, India
-
Raghuwanshi NS, Singh R, Reddy LS (2006) Runoff and Sediment Yield Modeling Using Artificial Neural Networks: Upper Siwane River, India. J Hydrol Eng 11:71–79. doi:10.1061/(ASCE)1084-0699(2006)11:1(71)
-
(2006)
J Hydrol Eng
, vol.11
, pp. 71-79
-
-
Raghuwanshi, N.S.1
Singh, R.2
Reddy, L.S.3
-
175
-
-
69049087742
-
Estimating daily pan evaporation using artificial neural network in a semi-arid environment
-
Rahimikhoob A (2009) Estimating daily pan evaporation using artificial neural network in a semi-arid environment. Theor Appl Climatol 98:101–105. doi:10.1007/s00704-008-0096-3
-
(2009)
Theor Appl Climatol
, vol.98
, pp. 101-105
-
-
Rahimikhoob, A.1
-
176
-
-
40549084354
-
Event-based sediment yield modeling using artificial neural network
-
Rai RK, Mathur BS (2008) Event-based sediment yield modeling using artificial neural network. Water Resour Manag 22:423–441. doi:10.1007/s11269-007-9170-3
-
(2008)
Water Resour Manag
, vol.22
, pp. 423-441
-
-
Rai, R.K.1
Mathur, B.S.2
-
177
-
-
79958862497
-
Wavelet and ANN combination model for prediction of daily suspended sediment load in rivers
-
Rajaee T (2011) Wavelet and ANN combination model for prediction of daily suspended sediment load in rivers. Sci Total Environ 409:2917–2928. doi:10.1016/j.scitotenv.2010.11.028
-
(2011)
Sci Total Environ
, vol.409
, pp. 2917-2928
-
-
Rajaee, T.1
-
178
-
-
0347135926
-
Modeling of the daily rainfall-runoff relationship with artificial neural network
-
Rajurkar MP, Kothyari UC, Chaube UC (2004) Modeling of the daily rainfall-runoff relationship with artificial neural network. J Hydrol 285:96–113. doi:10.1016/j.jhydrol.2003.08.011
-
(2004)
J Hydrol
, vol.285
, pp. 96-113
-
-
Rajurkar, M.P.1
Kothyari, U.C.2
Chaube, U.C.3
-
179
-
-
84885297245
-
Three-and-six-month-before forecast of water resources in a karst aquifer in the Terminio massif (Southern Italy)
-
Rampone S (2013) Three-and-six-month-before forecast of water resources in a karst aquifer in the Terminio massif (Southern Italy). Appl Soft Comput 13:4077–4086. doi:10.1016/j.asoc.2013.05.016
-
(2013)
Appl Soft Comput
, vol.13
, pp. 4077-4086
-
-
Rampone, S.1
-
180
-
-
0033842240
-
Measurement and estimation of actual evapotranspiration in the field under Mediterranean climate: A review
-
Rana G, Katerji N (2000) Measurement and estimation of actual evapotranspiration in the field under Mediterranean climate: A review. Eur J Agron 13:125–153. doi:10.1016/S1161-0301(00)00070-8
-
(2000)
Eur J Agron
, vol.13
, pp. 125-153
-
-
Rana, G.1
Katerji, N.2
-
181
-
-
65749094852
-
Runoff prediction using an integrated hybrid modelling scheme
-
Remesan R, Shamim MA, Han D, Mathew J (2009) Runoff prediction using an integrated hybrid modelling scheme. J Hydrol 372:48–60. doi:10.1016/j.jhydrol.2009.03.034
-
(2009)
J Hydrol
, vol.372
, pp. 48-60
-
-
Remesan, R.1
Shamim, M.A.2
Han, D.3
Mathew, J.4
-
182
-
-
15844383263
-
Representation of functional data in neural networks
-
Rossi F, Delannay N, Conan-Guez B, Verleysen M (2005) Representation of functional data in neural networks. Neurocomputing 64:183–210. doi:10.1016/j.neucom.2004.11.012
-
(2005)
Neurocomputing
, vol.64
, pp. 183-210
-
-
Rossi, F.1
Delannay, N.2
Conan-Guez, B.3
Verleysen, M.4
-
183
-
-
84871115737
-
A review on the applications of wavelet transform in hydrology time series analysis
-
Sang Y-F (2013) A review on the applications of wavelet transform in hydrology time series analysis. Atmos Res 122:8–15. doi:10.1016/j.atmosres.2012.11.003
-
(2013)
Atmos Res
, vol.122
, pp. 8-15
-
-
Sang, Y.-F.1
-
184
-
-
84868209993
-
Estimation of Daily Pan Evaporation Using Two Different Adaptive Neuro-Fuzzy Computing Techniques
-
Sanikhani H, Kisi O, Nikpour MR, Dinpashoh Y (2012) Estimation of Daily Pan Evaporation Using Two Different Adaptive Neuro-Fuzzy Computing Techniques. Water Resour Manag 26:4347–4365. doi:10.1007/s11269-012-0148-4
-
(2012)
Water Resour Manag
, vol.26
, pp. 4347-4365
-
-
Sanikhani, H.1
Kisi, O.2
Nikpour, M.R.3
Dinpashoh, Y.4
-
185
-
-
0034254025
-
A hybrid multi-model approach to river level forecasting
-
See L, Openshaw S (2000) A hybrid multi-model approach to river level forecasting. Hydrol Sci J 45:523–536. doi:10.1080/02626660009492354
-
(2000)
Hydrol Sci J
, vol.45
, pp. 523-536
-
-
See, L.1
Openshaw, S.2
-
186
-
-
68349123741
-
Bootstrap based artificial neural network (BANN) analysis for hierarchical prediction of monthly runoff in Upper Damodar Valley Catchment
-
Sharma SK, Tiwari KN (2009) Bootstrap based artificial neural network (BANN) analysis for hierarchical prediction of monthly runoff in Upper Damodar Valley Catchment. J Hydrol 374:209–222. doi:10.1016/j.jhydrol.2009.06.003
-
(2009)
J Hydrol
, vol.374
, pp. 209-222
-
-
Sharma, S.K.1
Tiwari, K.N.2
-
187
-
-
78149414268
-
Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model
-
Shiri J, Kisi O (2010) Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model. J Hydrol 394:486–493. doi:10.1016/j.jhydrol.2010.10.008
-
(2010)
J Hydrol
, vol.394
, pp. 486-493
-
-
Shiri, J.1
Kisi, O.2
-
188
-
-
21344444108
-
Predictability of river flow and suspended sediment transport in the Mississippi River basin: A non-linear deterministic approach
-
Sivakumar B, Wallender WW (2005) Predictability of river flow and suspended sediment transport in the Mississippi River basin: A non-linear deterministic approach. Earth Surf Process Landf 30:665–677. doi:10.1002/esp.1167
-
(2005)
Earth Surf Process Landf
, vol.30
, pp. 665-677
-
-
Sivakumar, B.1
Wallender, W.W.2
-
189
-
-
0037199712
-
River flow forecasting: Use of phase-space reconstruction and artificial neural networks approaches
-
Sivakumar B, Jayawardena AW, Fernando TMKG (2002) River flow forecasting: Use of phase-space reconstruction and artificial neural networks approaches. J Hydrol 265:225–245. doi:10.1016/S0022-1694(02)00112-9
-
(2002)
J Hydrol
, vol.265
, pp. 225-245
-
-
Sivakumar, B.1
Jayawardena, A.W.2
Fernando, T.M.K.G.3
-
190
-
-
84900858642
-
Monthly flow forecast for Mississippi River basin using artificial neural networks
-
Sivapragasam C, Vanitha S, Muttil N et al (2013) Monthly flow forecast for Mississippi River basin using artificial neural networks. Neural Comput Applic. doi:10.1007/s00521-013-1419-6
-
(2013)
Neural Comput Applic
-
-
Sivapragasam, C.1
Vanitha, S.2
Muttil, N.3
-
191
-
-
0029416249
-
Neural-network models of rainfall-runoff process
-
Smith J, Eli RN (1995) Neural-network models of rainfall-runoff process. J Water Resour Plan Manag 121:499–508
-
(1995)
J Water Resour Plan Manag
, vol.121
, pp. 499-508
-
-
Smith, J.1
Eli, R.N.2
-
192
-
-
0035698908
-
Stochastic generation of annual, monthly and daily climate data: A review
-
Srikanthan R, McMahon TA (2001) Stochastic generation of annual, monthly and daily climate data: A review. Hydrol Earth Syst Sci 5:653–670. doi:10.5194/hess-5-653-2001
-
(2001)
Hydrol Earth Syst Sci
, vol.5
, pp. 653-670
-
-
Srikanthan, R.1
McMahon, T.A.2
-
193
-
-
0036843660
-
Modelling evaporation using an artificial neural network algorithm
-
Sudheer K, Gosain A, Mohana Rangan D, Saheb S (2002) Modelling evaporation using an artificial neural network algorithm. Hydrol Process 16:3189–3202
-
(2002)
Hydrol Process
, vol.16
, pp. 3189-3202
-
-
Sudheer, K.1
Gosain, A.2
Mohana Rangan, D.3
Saheb, S.4
-
194
-
-
79960702239
-
Improved water level forecasting performance by using optimal steepness coefficients in an artificial neural network
-
Sulaiman M, El-Shafie A, Karim O, Basri H (2011) Improved water level forecasting performance by using optimal steepness coefficients in an artificial neural network. Water Resour Manag 25:2525–2541
-
(2011)
Water Resour Manag
, vol.25
, pp. 2525-2541
-
-
Sulaiman, M.1
El-Shafie, A.2
Karim, O.3
Basri, H.4
-
195
-
-
84860356830
-
Influence of lag time on event-based rainfall-runoff modeling using the data driven approach
-
Talei A, Chua LHC (2012) Influence of lag time on event-based rainfall-runoff modeling using the data driven approach. J Hydrol 438–439:223–233. doi:10.1016/j.jhydrol.2012.03.027
-
(2012)
J Hydrol
, vol.438-439
, pp. 223-233
-
-
Talei, A.1
Chua, L.H.C.2
-
196
-
-
84886101097
-
Runoff forecasting using a Takagi-Sugeno neuro-fuzzy model with online learning
-
Talei A, Chua LHC, Quek C, Jansson PE (2013) Runoff forecasting using a Takagi-Sugeno neuro-fuzzy model with online learning. J Hydrol 488:17–32. doi:10.1016/j.jhydrol.2013.02.022
-
(2013)
J Hydrol
, vol.488
, pp. 17-32
-
-
Talei, A.1
Chua, L.H.C.2
Quek, C.3
Jansson, P.E.4
-
197
-
-
84876429805
-
Principle Component Analysis in Conjuction with Data Driven Methods for Sediment Load Prediction
-
Tayfur G, Karimi Y, Singh VP (2013) Principle Component Analysis in Conjuction with Data Driven Methods for Sediment Load Prediction. Water Resour Manag 27:2541–2554. doi:10.1007/s11269-013-0302-7
-
(2013)
Water Resour Manag
, vol.27
, pp. 2541-2554
-
-
Tayfur, G.1
Karimi, Y.2
Singh, V.P.3
-
198
-
-
84874093730
-
Application of artificial neural networks and multiple linear regression to forecast monthly river flow in Turkey
-
Terzi Ö, Önal S (2012) Application of artificial neural networks and multiple linear regression to forecast monthly river flow in Turkey. Afr J Agric Res 7:1317–1323. doi:10.5897/AJAR11.1426
-
(2012)
Afr J Agric Res
, vol.7
, pp. 1317-1323
-
-
Terzi, Ö.1
Önal, S.2
-
199
-
-
84964500382
-
An Approach Toward a Rational Classification of Climate
-
Thornthwaite CW (1948) An Approach Toward a Rational Classification of Climate. Soil Sci 66:77
-
(1948)
Soil Sci
, vol.66
, pp. 77
-
-
Thornthwaite, C.W.1
-
200
-
-
78149408167
-
Development of an accurate and reliable hourly flood forecasting model using wavelet–bootstrap–ANN (WBANN) hybrid approach
-
Tiwari MK, Chatterjee C (2010) Development of an accurate and reliable hourly flood forecasting model using wavelet–bootstrap–ANN (WBANN) hybrid approach. J Hydrol 394:458–470. doi:10.1016/j.jhydrol.2010.10.001
-
(2010)
J Hydrol
, vol.394
, pp. 458-470
-
-
Tiwari, M.K.1
Chatterjee, C.2
-
202
-
-
37549066943
-
Multistep ahead streamflow forecasting: Role of calibration data in conceptual and neural network modeling
-
Toth E, Brath A (2007) Multistep ahead streamflow forecasting: Role of calibration data in conceptual and neural network modeling. Water Resour Res 43. doi: 10.1029/2006WR005383
-
(2007)
Water Resour Res
, pp. 43
-
-
Toth, E.1
Brath, A.2
-
203
-
-
23044444044
-
Temperature-Based Approaches for Estimating Reference Evapotranspiration
-
Trajkovic S (2005) Temperature-Based Approaches for Estimating Reference Evapotranspiration. J Irrig Drain Eng 131:316–323. doi:10.1061/(ASCE)0733-9437(2005)131:4(316)
-
(2005)
J Irrig Drain Eng
, vol.131
, pp. 316-323
-
-
Trajkovic, S.1
-
204
-
-
76549126637
-
Artificial neural network for modeling reference evapotranspiration complex process in Sudano-Sahelian zone
-
Traore S, Wang Y-M, Kerh T (2010) Artificial neural network for modeling reference evapotranspiration complex process in Sudano-Sahelian zone. Agric Water Manag 97:707–714. doi:10.1016/j.agwat.2010.01.002
-
(2010)
Agric Water Manag
, vol.97
, pp. 707-714
-
-
Traore, S.1
Wang, Y.-M.2
Kerh, T.3
-
205
-
-
84859303352
-
Application of artificial neural networks and adaptive neuro-fuzzy inference system models to short-term streamflow forecasting
-
Vafakhah M (2012) Application of artificial neural networks and adaptive neuro-fuzzy inference system models to short-term streamflow forecasting. Can J Civ Eng 39:402–414. doi:10.1139/l2012-011
-
(2012)
Can J Civ Eng
, vol.39
, pp. 402-414
-
-
Vafakhah, M.1
-
206
-
-
84870999624
-
Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir
-
Valipour M, Banihabib ME, Behbahani SMR (2013) Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir. J Hydrol 476:433–441. doi:10.1016/j.jhydrol.2012.11.017
-
(2013)
J Hydrol
, vol.476
, pp. 433-441
-
-
Valipour, M.1
Banihabib, M.E.2
Behbahani, S.M.R.3
-
207
-
-
84878770211
-
Forecasting the level of reservoirs using multiple input fuzzification in ANFIS
-
Valizadeh N, El-Shafie A (2013) Forecasting the level of reservoirs using multiple input fuzzification in ANFIS. Water Resour Manag 27:3319–3331
-
(2013)
Water Resour Manag
, vol.27
, pp. 3319-3331
-
-
Valizadeh, N.1
El-Shafie, A.2
-
208
-
-
33646547633
-
Forecasting daily streamflow using hybrid ANN models
-
Wang W, Van Gelder PHAJM, Vrijling JK, Ma J (2006) Forecasting daily streamflow using hybrid ANN models. J Hydrol 324:383–399. doi:10.1016/j.jhydrol.2005.09.032
-
(2006)
J Hydrol
, vol.324
, pp. 383-399
-
-
Wang, W.1
Van Gelder, P.H.A.J.M.2
Vrijling, J.K.3
Ma, J.4
-
209
-
-
68349105875
-
A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series
-
Wang WC, Chau KW, Cheng CT, Qiu L (2009) A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series. J Hydrol 374:294–306. doi:10.1016/j.jhydrol.2009.06.019
-
(2009)
J Hydrol
, vol.374
, pp. 294-306
-
-
Wang, W.C.1
Chau, K.W.2
Cheng, C.T.3
Qiu, L.4
-
210
-
-
79951800404
-
A hybrid neural network model for cyanobacteria bloom in Dianchi Lake
-
Wang Z, Huang K, Zhou PJ, Guo HC (2010) A hybrid neural network model for cyanobacteria bloom in Dianchi Lake. Procedia Environ Sci 2:67–75. doi:10.1016/j.proenv.2010.10.010
-
(2010)
Procedia Environ Sci
, vol.2
, pp. 67-75
-
-
Wang, Z.1
Huang, K.2
Zhou, P.J.3
Guo, H.C.4
-
211
-
-
80052953523
-
Flood simulation using parallel genetic algorithm integrated wavelet neural networks
-
Wang Y, Wang H, Lei X et al (2011) Flood simulation using parallel genetic algorithm integrated wavelet neural networks. Neurocomputing 74:2734–2744. doi:10.1016/j.neucom.2011.03.018
-
(2011)
Neurocomputing
, vol.74
, pp. 2734-2744
-
-
Wang, Y.1
Wang, H.2
Lei, X.3
-
212
-
-
84874761795
-
A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows
-
Wei S, Yang H, Song J et al (2013) A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows. Hydrol Sci J 58:374–389. doi:10.1080/02626667.2012.754102
-
(2013)
Hydrol Sci J
, vol.58
, pp. 374-389
-
-
Wei, S.1
Yang, H.2
Song, J.3
-
213
-
-
34748907750
-
Adaptive fuzzy modeling versus artificial neural networks
-
Wieland R, Mirschel W (2008) Adaptive fuzzy modeling versus artificial neural networks. Environ Model Softw 23:215–224. doi:10.1016/j.envsoft.2007.06.004
-
(2008)
Environ Model Softw
, vol.23
, pp. 215-224
-
-
Wieland, R.1
Mirschel, W.2
-
214
-
-
72249118415
-
A new library to combine artificial neural networks and support vector machines with statistics and a database engine for application in environmental modeling
-
Wieland R, Mirschel W, Zbell B et al (2010) A new library to combine artificial neural networks and support vector machines with statistics and a database engine for application in environmental modeling. Environ Model Softw 25:412–420. doi:10.1016/j.envsoft.2009.11.006
-
(2010)
Environ Model Softw
, vol.25
, pp. 412-420
-
-
Wieland, R.1
Mirschel, W.2
Zbell, B.3
-
215
-
-
0004779144
-
Daily and Seasonal Evapotranspiration and Yield of Irrigated Alfalfa in Southern Idaho
-
Wright JL (1988) Daily and Seasonal Evapotranspiration and Yield of Irrigated Alfalfa in Southern Idaho. Agron J 80:662. doi:10.2134/agronj1988.00021962008000040022x
-
(1988)
Agron J
, vol.80
, pp. 662
-
-
Wright, J.L.1
-
216
-
-
77958035437
-
Data-driven models for monthly streamflow time series prediction
-
Wu CL, Chau KW (2010) Data-driven models for monthly streamflow time series prediction. Eng Appl Artif Intell 23:1350–1367. doi:10.1016/j.engappai.2010.04.003
-
(2010)
Eng Appl Artif Intell
, vol.23
, pp. 1350-1367
-
-
Wu, C.L.1
Chau, K.W.2
-
217
-
-
79952006341
-
Rainfall-runoff modeling using artificial neural network coupled with singular spectrum analysis
-
Wu CL, Chau KW (2011) Rainfall-runoff modeling using artificial neural network coupled with singular spectrum analysis. J Hydrol 399:394–409. doi:10.1016/j.jhydrol.2011.01.017
-
(2011)
J Hydrol
, vol.399
, pp. 394-409
-
-
Wu, C.L.1
Chau, K.W.2
-
218
-
-
84873992358
-
Prediction of rainfall time series using modular soft computing methods
-
Wu CL, Chau KW (2013) Prediction of rainfall time series using modular soft computing methods. Eng Appl Artif Intell 26:997–1007. doi:10.1016/j.engappai.2012.05.023
-
(2013)
Eng Appl Artif Intell
, vol.26
, pp. 997-1007
-
-
Wu, C.L.1
Chau, K.W.2
-
219
-
-
18744366631
-
Artificial Neural Networks for Forecasting Watershed Runoff and Stream Flows
-
Wu JS, Han J, Annambhotla S, Bryant S (2005) Artificial Neural Networks for Forecasting Watershed Runoff and Stream Flows. J Hydrol Eng 10:216–222. doi:10.1061/(ASCE)1084-0699(2005)10:3(216)
-
(2005)
J Hydrol Eng
, vol.10
, pp. 216-222
-
-
Wu, J.S.1
Han, J.2
Annambhotla, S.3
Bryant, S.4
-
220
-
-
70349777454
-
Predicting monthly streamflow using data-driven models coupled with data-preprocessing techniques
-
Wu CL, Chau KW, Li YS (2009a) Predicting monthly streamflow using data-driven models coupled with data-preprocessing techniques. Water Resour Res 45:1–23. doi:10.1029/2007WR006737
-
(2009)
Water Resour Res
, vol.45
, pp. 1-23
-
-
Wu, C.L.1
Chau, K.W.2
Li, Y.S.3
-
221
-
-
65749118118
-
Methods to improve neural network performance in daily flows prediction
-
Wu CL, Chau KW, Li YS (2009b) Methods to improve neural network performance in daily flows prediction. J Hydrol 372:80–93. doi:10.1016/j.jhydrol.2009.03.038
-
(2009)
J Hydrol
, vol.372
, pp. 80-93
-
-
Wu, C.L.1
Chau, K.W.2
Li, Y.S.3
-
222
-
-
77954384622
-
Prediction of rainfall time series using modular artificial neural networks coupled with data-preprocessing techniques
-
Wu CL, Chau KW, Fan C (2010) Prediction of rainfall time series using modular artificial neural networks coupled with data-preprocessing techniques. J Hydrol 389:146–167. doi:10.1016/j.jhydrol.2010.05.040
-
(2010)
J Hydrol
, vol.389
, pp. 146-167
-
-
Wu, C.L.1
Chau, K.W.2
Fan, C.3
-
223
-
-
84857365593
-
Multi-label classification models for sustainable flood retention basins
-
Yang Q, Shao J, Scholz M et al (2012) Multi-label classification models for sustainable flood retention basins. Environ Model Softw 32:27–36. doi:10.1016/j.envsoft.2012.01.001
-
(2012)
Environ Model Softw
, vol.32
, pp. 27-36
-
-
Yang, Q.1
Shao, J.2
Scholz, M.3
-
224
-
-
84933545314
-
RBFNN versus FFNN for daily river flow forecasting at Johor River, Malaysia
-
Yaseen ZM, El-Shafie A, Afan HA et al (2015a) RBFNN versus FFNN for daily river flow forecasting at Johor River, Malaysia. Neural Comput Applic. doi:10.1007/s00521-015-1952-6
-
(2015)
Neural Comput Applic
-
-
Yaseen, Z.M.1
El-Shafie, A.2
Afan, H.A.3
-
225
-
-
84945157492
-
Artificial intelligence based models for stream-flow forecasting: 2000–2015
-
Yaseen ZM, El-shafie A, Jaafar O et al (2015b) Artificial intelligence based models for stream-flow forecasting: 2000–2015. J Hydrol 530:829–844. doi:10.1016/j.jhydrol.2015.10.038
-
(2015)
J Hydrol
, vol.530
, pp. 829-844
-
-
Yaseen, Z.M.1
El-shafie, A.2
Jaafar, O.3
-
226
-
-
80054871623
-
Catchment flow estimation using Artificial Neural Networks in the mountainous Euphrates Basin
-
Yilmaz AG, Imteaz MA, Jenkins G (2011) Catchment flow estimation using Artificial Neural Networks in the mountainous Euphrates Basin. J Hydrol 410:134–140. doi:10.1016/j.jhydrol.2011.09.031
-
(2011)
J Hydrol
, vol.410
, pp. 134-140
-
-
Yilmaz, A.G.1
Imteaz, M.A.2
Jenkins, G.3
-
227
-
-
77953342831
-
Comparing Sigmoid Transfer Functions for Neural Network Multistep Ahead Streamflow Forecasting
-
Yonaba H, Anctil F, Fortin V (2010) Comparing Sigmoid Transfer Functions for Neural Network Multistep Ahead Streamflow Forecasting. J Hydrol Eng 15:275–283. doi:10.1061/(ASCE)HE.1943-5584.0000188
-
(2010)
J Hydrol Eng
, vol.15
, pp. 275-283
-
-
Yonaba, H.1
Anctil, F.2
Fortin, V.3
-
228
-
-
78650179085
-
A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer
-
Yoon H, Jun S-C, Hyun Y et al (2011) A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer. J Hydrol 396:128–138. doi:10.1016/j.jhydrol.2010.11.002
-
(2011)
J Hydrol
, vol.396
, pp. 128-138
-
-
Yoon, H.1
Jun, S.-C.2
Hyun, Y.3
-
229
-
-
33750311824
-
Multiple recurrent neural networks for stable adaptive control
-
Yu W (2006) Multiple recurrent neural networks for stable adaptive control. Neurocomputing 70:430–444. doi:10.1016/j.neucom.2005.12.122
-
(2006)
Neurocomputing
, vol.70
, pp. 430-444
-
-
Yu, W.1
-
230
-
-
33947362356
-
Estimating Evapotranspiration Using Artificial Neural Network and Minimum Climatological Data
-
Zanetti SS, Sousa EF, Oliveira VP et al (2007) Estimating Evapotranspiration Using Artificial Neural Network and Minimum Climatological Data. J Irrig Drain Eng 133:83–89. doi:10.1061/(ASCE)0733-9437(2007)133:2(83)
-
(2007)
J Irrig Drain Eng
, vol.133
, pp. 83-89
-
-
Zanetti, S.S.1
Sousa, E.F.2
Oliveira, V.P.3
-
231
-
-
0033019602
-
Short term streamflow forecasting using artificial neural networks
-
Zealand CM, Burn DH, Simonovic SP (1999) Short term streamflow forecasting using artificial neural networks. J Hydrol 214:32–48. doi:10.1016/S0022-1694(98)00242-X
-
(1999)
J Hydrol
, vol.214
, pp. 32-48
-
-
Zealand, C.M.1
Burn, D.H.2
Simonovic, S.P.3
-
232
-
-
84863091632
-
A toy model for monthly river flow forecasting
-
Zeng X, Kiviat KL, Sakaguchi K, Mahmoud AMA (2012) A toy model for monthly river flow forecasting. J Hydrol 452–453:226–231. doi:10.1016/j.jhydrol.2012.05.053
-
(2012)
J Hydrol
, vol.452-453
, pp. 226-231
-
-
Zeng, X.1
Kiviat, K.L.2
Sakaguchi, K.3
Mahmoud, A.M.A.4
-
233
-
-
0037466126
-
Geomorphology-based artificial neural networks (GANNs) for estimation of direct runoff over watersheds
-
Zhang B, Govindaraju RS (2003) Geomorphology-based artificial neural networks (GANNs) for estimation of direct runoff over watersheds. J Hydrol 273:18–34. doi:10.1016/S0022-1694(02)00313-X
-
(2003)
J Hydrol
, vol.273
, pp. 18-34
-
-
Zhang, B.1
Govindaraju, R.S.2
-
234
-
-
80054678981
-
Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting
-
Zhang X, Liang F, Yu B, Zong Z (2011) Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting. J Hydrol 409:696–709. doi:10.1016/j.jhydrol.2011.09.002
-
(2011)
J Hydrol
, vol.409
, pp. 696-709
-
-
Zhang, X.1
Liang, F.2
Yu, B.3
Zong, Z.4
-
235
-
-
84886728620
-
Performance of radial basis and LM-feed forward artificial neural networks for predicting daily watershed runoff
-
Zounemat-Kermani M, Kisi O, Rajaee T (2013) Performance of radial basis and LM-feed forward artificial neural networks for predicting daily watershed runoff. Appl Soft Comput J 13:4633–4644. doi:10.1016/j.asoc.2013.07.007
-
(2013)
Appl Soft Comput J
, vol.13
, pp. 4633-4644
-
-
Zounemat-Kermani, M.1
Kisi, O.2
Rajaee, T.3
|