-
1
-
-
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
-
2
-
-
84964727663
-
Prediction of daily dewpoint temperature using a model combining the support vector machine with firefly algorithm
-
et al
-
Al-Shammari ET, Mohammadi K, Keivani A et al (2016) Prediction of daily dewpoint temperature using a model combining the support vector machine with firefly algorithm. J Irrig Drain Eng. doi:10.1061/(ASCE)IR.1943-4774.0001015
-
(2016)
J Irrig Drain Eng
-
-
Al-Shammari, E.T.1
Mohammadi, K.2
Keivani, A.3
-
3
-
-
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
-
4
-
-
70350070851
-
A comparative study for estimation of wave height using traditional and hybrid soft-computing methods
-
Cekaite A (2016) A comparative study for estimation of wave height using traditional and hybrid soft-computing methods. Int J Comput Collab Learn 4:319–341. doi:10.1007/s11412-009-9067-7
-
(2016)
Int J Comput Collab Learn
, vol.4
, pp. 319-341
-
-
Cekaite, A.1
-
5
-
-
84893812050
-
A Support Vector Machine-Firefly Algorithm based forecasting model to determine malaria transmission
-
Ch S, Sohani SK, Kumar D et al (2014) A Support Vector Machine-Firefly Algorithm based forecasting model to determine malaria transmission. Neurocomputing 129:279–288. doi:10.1016/j.neucom.2013.09.030
-
(2014)
Neurocomputing
, vol.129
, pp. 279-288
-
-
Ch, S.1
Sohani, S.K.2
Kumar, D.3
-
6
-
-
84903642315
-
Root mean square error (RMSE) or mean absolute error (MAE)?—arguments against avoiding RMSE in the literature
-
Chai T, Draxler RR (2014) Root mean square error (RMSE) or mean absolute error (MAE)?—arguments against avoiding RMSE in the literature. Geosci Model Dev 7:1247–1250. doi:10.5194/gmd-7-1247-2014
-
(2014)
Geosci Model Dev
, vol.7
, pp. 1247-1250
-
-
Chai, T.1
Draxler, R.R.2
-
7
-
-
84928136722
-
Application of the artificial neural network model for prediction of monthly standardized precipitation and evapotranspiration index using hydrometeorological parameters and climate indices in eastern Australia
-
Deo RC, Şahin M (2015) Application of the artificial neural network model for prediction of monthly standardized precipitation and evapotranspiration index using hydrometeorological parameters and climate indices in eastern Australia. Atmos Res 161–162:65–81. doi:10.1016/j.atmosres.2015.03.018
-
(2015)
Atmos Res
, vol.161-162
, pp. 65-81
-
-
Deo, R.C.1
Şahin, M.2
-
8
-
-
85017512971
-
Forecasting evaporative loss by least-square support-vector regression and evaluation with genetic programming, Gaussian process, and minimax probability machine regression: case study of Brisbane City
-
Deo RC, Samui P (2017) Forecasting evaporative loss by least-square support-vector regression and evaluation with genetic programming, Gaussian process, and minimax probability machine regression: case study of Brisbane City. J Hydrol Eng 22:5017003. doi:10.1061/(ASCE)HE.1943-5584.0001506
-
(2017)
J Hydrol Eng
, vol.22
, pp. 5017003
-
-
Deo, R.C.1
Samui, P.2
-
9
-
-
84941335923
-
Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models
-
Deo RC, Samui P, Kim D (2015) Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models. Stoch Environ Res Risk Assess. doi:10.1007/s00477-015-1153-y
-
(2015)
Stoch Environ Res Risk Assess
-
-
Deo, R.C.1
Samui, P.2
Kim, D.3
-
10
-
-
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
-
11
-
-
84899013173
-
Support vector regression machines
-
Drucker H, Burges CJ, Kaufman L, Smola AJ, Vapnik V (1997) Support vector regression machines. Adv Neural Inf Process Syst 155–161
-
(1997)
Adv Neural Inf Process Syst
, pp. 155-161
-
-
Drucker, H.1
Burges, C.J.2
Kaufman, L.3
Smola, A.J.4
Vapnik, V.5
-
12
-
-
84957593712
-
Application of soft computing based hybrid models in hydrological variables modeling: A comprehensive review
-
Fahimi F, Yaseen ZM, El-shafie A (2017) Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review. Theor Appl Climatol 128 (3–4): 875 – 903
-
(2017)
Theor Appl Climatol
, vol.128
, Issue.3-4
, pp. 875-903
-
-
Fahimi, F.1
Yaseen, Z.M.2
El-Shafie, A.3
-
13
-
-
84884589096
-
Relative importance of parameters affecting wind speed prediction using artificial neural networks
-
Ghorbani MA, Khatibi R, Hosseini B, Bilgili M (2013) Relative importance of parameters affecting wind speed prediction using artificial neural networks. Theor Appl Climatol 114:107–114. doi:10.1007/s00704-012-0821-9
-
(2013)
Theor Appl Climatol
, vol.114
, pp. 107-114
-
-
Ghorbani, M.A.1
Khatibi, R.2
Hosseini, B.3
Bilgili, M.4
-
14
-
-
84961195082
-
A comparative study of artificial neural network (MLP, RBF) and support vector machine models for river flow prediction
-
Ghorbani MA, Zadeh HA, Isazadeh M, Terzi O (2016) A comparative study of artificial neural network (MLP, RBF) and support vector machine models for river flow prediction. Environ Earth Sci 75:1–14. doi:10.1007/s12665-015-5096-x
-
(2016)
Environ Earth Sci
, vol.75
, pp. 1-14
-
-
Ghorbani, M.A.1
Zadeh, H.A.2
Isazadeh, M.3
Terzi, O.4
-
15
-
-
85019152630
-
Application of firefly algorithm-based support vector machines for prediction of field capacity and permanent wilting point
-
Ghorbani MA, Shamshirband S, Zare Haghi D et al (2017) Application of firefly algorithm-based support vector machines for prediction of field capacity and permanent wilting point. Soil Tillage Res 172:32–38. doi:10.1016/j.still.2017.04.009
-
(2017)
Soil Tillage Res
, vol.172
, pp. 32-38
-
-
Ghorbani, M.A.1
Shamshirband, S.2
Zare Haghi, D.3
-
17
-
-
84924272182
-
Soft computing approaches for forecasting reference evapotranspiration
-
Gocić M, Motamedi S, Shamshirband S et al (2015) Soft computing approaches for forecasting reference evapotranspiration. Comput Electron Agric 113:164–173. doi:10.1016/j.compag.2015.02.010
-
(2015)
Comput Electron Agric
, vol.113
, pp. 164-173
-
-
Gocić, M.1
Motamedi, S.2
Shamshirband, S.3
-
18
-
-
84898464831
-
Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS
-
Goyal MK, Bharti B, Quilty J et al (2014) Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS. Expert Syst Appl 41:5267–5276. doi:10.1016/j.eswa.2014.02.047
-
(2014)
Expert Syst Appl
, vol.41
, pp. 5267-5276
-
-
Goyal, M.K.1
Bharti, B.2
Quilty, J.3
-
19
-
-
84956852398
-
Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: case of Turkey
-
Günay ME (2016) Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: case of Turkey. Energy Policy 90:92–101. doi:10.1016/j.enpol.2015.12.019
-
(2016)
Energy Policy
, vol.90
, pp. 92-101
-
-
Günay, M.E.1
-
20
-
-
84860700128
-
A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm
-
IEEE, Penang
-
Hassanzadeh T, Faez K, Seyfi G (2012) A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm. In Biomedical Engineering (ICoBE), 2012 International Conference on (pp. 63–67). IEEE, Penang. doi:10.1109/ICoBE.2012.6178956
-
(2012)
Biomedical Engineering (Icobe), 2012 International Conference On
, pp. 63-67
-
-
Hassanzadeh, T.1
Faez, K.2
Seyfi, G.3
-
21
-
-
84893700335
-
Methods for uncertainty assessment of climate models and model predictions over East Asia
-
et al
-
Heo K-Y, Ha K-J, Yun K-S et al (2013) Methods for uncertainty assessment of climate models and model predictions over East Asia. Int J Climatol. doi:10.1002/joc.3692
-
(2013)
Int J Climatol
-
-
Heo, K.-Y.1
Ha, K.-J.2
Yun, K.-S.3
-
22
-
-
67650639040
-
Hybrid evolutionary algorithms in a SVR-based electric load forecasting model
-
Hong W-C (2009) Hybrid evolutionary algorithms in a SVR-based electric load forecasting model. Int J Electr Power Energy Syst 31:409–417. doi:10.1016/j.ijepes.2009.03.020
-
(2009)
Int J Electr Power Energy Syst
, vol.31
, pp. 409-417
-
-
Hong, W.-C.1
-
23
-
-
84943393747
-
A practical guide to support vector classification
-
Hsu C-W, Chang C-C, Lin C-J (2008) A practical guide to support vector classification. BJU Int 101:1396–1400. doi:10.1177/02632760022050997
-
(2008)
BJU Int
, vol.101
, pp. 1396-1400
-
-
Hsu, C.-W.1
Chang, C.-C.2
Lin, C.-J.3
-
25
-
-
34147216758
-
Climate change 2007: the physical science basis
-
IPCC (2007) Climate change 2007: the physical science basis. Intergov Panel Clim Chang 446:727–728. doi:10.1038/446727a
-
(2007)
Intergov Panel Clim Chang
, vol.446
, pp. 727-728
-
-
-
26
-
-
84973901088
-
Integrating firefly algorithm in artificial neural network models for accurate software cost predictions
-
Kaushik A, Tayal DK, Yadav K, Kaur A (2016) Integrating firefly algorithm in artificial neural network models for accurate software cost predictions. J Softw Evol Process 28:665–688. doi:10.1002/smr.1792
-
(2016)
J Softw Evol Process
, vol.28
, pp. 665-688
-
-
Kaushik, A.1
Tayal, D.K.2
Yadav, K.3
Kaur, A.4
-
27
-
-
84899800725
-
A new hybrid modified firefly algorithm and support vector regression model for accurate short term load forecasting
-
Kavousi-Fard A, Samet H, Marzbani F (2014) A new hybrid modified firefly algorithm and support vector regression model for accurate short term load forecasting. Expert Syst Appl 41:6047–6056. doi:10.1016/j.eswa.2014.03.053
-
(2014)
Expert Syst Appl
, vol.41
, pp. 6047-6056
-
-
Kavousi-Fard, A.1
Samet, H.2
Marzbani, F.3
-
29
-
-
84977083335
-
A nonlinear mathematical modeling of daily pan evaporation based on conjugate gradient method
-
Keshtegar B, Piri J, Kisi O (2016) A nonlinear mathematical modeling of daily pan evaporation based on conjugate gradient method. Comput Electron Agric 127:120–130. doi:10.1016/j.compag.2016.05.018
-
(2016)
Comput Electron Agric
, vol.127
, pp. 120-130
-
-
Keshtegar, B.1
Piri, J.2
Kisi, O.3
-
30
-
-
69049111816
-
Estimating daily pan evaporation using adaptive neural-based fuzzy inference system
-
Keskin ME, Terzi Ö, Taylan D (2009) Estimating daily pan evaporation using adaptive neural-based fuzzy inference system. Theor Appl Climatol 98:79–87. doi:10.1007/s00704-008-0092-7
-
(2009)
Theor Appl Climatol
, vol.98
, pp. 79-87
-
-
Keskin, M.E.1
Terzi, Ö.2
Taylan, D.3
-
31
-
-
33748933705
-
Daily pan evaporation modelling using a neuro-fuzzy computing technique
-
Kişi Ö (2006) Daily pan evaporation modelling using a neuro-fuzzy computing technique. J Hydrol 329:636–646. doi:10.1016/j.jhydrol.2006.03.015
-
(2006)
J Hydrol
, vol.329
, pp. 636-646
-
-
Kişi, Ö.1
-
32
-
-
34447337473
-
Evapotranspiration modelling from climatic data using a neural computing technique
-
Kisi O (2007) Evapotranspiration modelling from climatic data using a neural computing technique. Hydrol Process 21:1925–1934. doi:10.1002/hyp.6403
-
(2007)
Hydrol Process
, vol.21
, pp. 1925-1934
-
-
Kisi, O.1
-
33
-
-
84960423143
-
Daily pan evaporation modeling using chi-squared automatic interaction detector, neural networks, classification and regression tree
-
Kisi O, Genc O, Dinc S, Zounemat-Kermani M (2016) Daily pan evaporation modeling using chi-squared automatic interaction detector, neural networks, classification and regression tree. Comput Electron Agric 122:112–117. doi:10.1016/j.compag.2016.01.026
-
(2016)
Comput Electron Agric
, vol.122
, pp. 112-117
-
-
Kisi, O.1
Genc, O.2
Dinc, S.3
Zounemat-Kermani, M.4
-
34
-
-
84962783538
-
Forecasting daily streamflow using online sequential extreme learning machines
-
Lima AR, Cannon AJ, Hsieh WW (2016) Forecasting daily streamflow using online sequential extreme learning machines. J Hydrol 537:431–443. doi:10.1016/j.jhydrol.2016.03.017
-
(2016)
J Hydrol
, vol.537
, pp. 431-443
-
-
Lima, A.R.1
Cannon, A.J.2
Hsieh, W.W.3
-
35
-
-
84872509836
-
A study on sigmoid kernels for SVM and the training of non-PSD kernels by SMO-type methods
-
Lin HT, Lin CJ (2003) A study on sigmoid kernels for SVM and the training of non-PSD kernels by SMO-type methods. Neural Comput 1–32
-
(2003)
Neural Comput
, pp. 1-32
-
-
Lin, H.T.1
Lin, C.J.2
-
36
-
-
70450219535
-
Firefly algorithm for continuous constrained optimization tasks
-
Lukasik S, Zak S (2009) Firefly algorithm for continuous constrained optimization tasks. Firefly Algorithm Contin Constrained Optim Tasks 5796:97–106. doi:10.1007/978-3-642-04441-0_8
-
(2009)
Firefly Algorithm Contin Constrained Optim Tasks
, vol.5796
, pp. 97-106
-
-
Lukasik, S.1
Zak, S.2
-
37
-
-
84867013911
-
An improved evaporation dome for forest environments
-
Macfarlane C, Ogden GN (2012) An improved evaporation dome for forest environments. Comput Electron Agric 89:126–129. doi:10.1016/j.compag.2012.09.004
-
(2012)
Comput Electron Agric
, vol.89
, pp. 126-129
-
-
Macfarlane, C.1
Ogden, G.N.2
-
38
-
-
84964054524
-
Application of artificial neural network for predicting hourly indoor air temperature and relative humidity in modern building in humid region
-
Mba L, Meukam P, Kemajou A (2016) Application of artificial neural network for predicting hourly indoor air temperature and relative humidity in modern building in humid region. Energy Build 121:32–42. doi:10.1016/j.enbuild.2016.03.046
-
(2016)
Energy Build
, vol.121
, pp. 32-42
-
-
Mba, L.1
Meukam, P.2
Kemajou, A.3
-
39
-
-
0003444652
-
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
-
344
-
McClelland JL, Rumelhart DE (1988) Explorations in parallel distributed processing: a handbook of models, programs, and exercises. Explor Parallel Distrib Process Handb Model Programs Exerc 344:ix, 344. doi:10.2307/1423065
-
(1988)
Explor Parallel Distrib Process Handb Model Programs Exerc
, vol.344
, pp. 9
-
-
McClelland, J.L.1
Rumelhart, D.E.2
-
40
-
-
67650621579
-
Application and analysis of support vector machine based simulation for runoff and sediment yield
-
Misra D, Oommen T, Agarwal A et al (2009) Application and analysis of support vector machine based simulation for runoff and sediment yield. Biosyst Eng 103:527–535. doi:10.1016/j.biosystemseng.2009.04.017
-
(2009)
Biosyst Eng
, vol.103
, pp. 527-535
-
-
Misra, D.1
Oommen, T.2
Agarwal, A.3
-
41
-
-
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
-
42
-
-
84944683850
-
Using artificial neural network approach for simultaneous forecasting of weekly groundwater levels at multiple sites
-
Mohanty S, Jha MK, Raul SK et al (2015) Using artificial neural network approach for simultaneous forecasting of weekly groundwater levels at multiple sites. Water Resour Manag 29:5521–5532. doi:10.1007/s11269-015-1132-6
-
(2015)
Water Resour Manag
, vol.29
, pp. 5521-5532
-
-
Mohanty, S.1
Jha, M.K.2
Raul, S.K.3
-
43
-
-
0014776873
-
River flow forecasting through conceptual models part I—a discussion of principles
-
Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I—a discussion of principles. J Hydrol 10:282–290. doi:10.1016/0022-1694(70)90255-6
-
(1970)
J Hydrol
, vol.10
, pp. 282-290
-
-
Nash, J.E.1
Sutcliffe, J.V.2
-
44
-
-
84966632250
-
A novel method to water level prediction using RBF and FFA
-
Soleymani SA, Goudarzi S, Anisi MH et al (2016) A novel method to water level prediction using RBF and FFA. Water Resour Manag:1–19. doi:10.1007/s11269-016-1347-1
-
(2016)
Water Resour Manag
, pp. 1-19
-
-
Soleymani, S.A.1
Goudarzi, S.2
Anisi, M.H.3
-
45
-
-
0034962651
-
Summarizing multiple aspects of model performance in a single diagram
-
Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos 106:7183–7192. doi:10.1029/2000JD900719
-
(2001)
J Geophys Res Atmos
, vol.106
, pp. 7183-7192
-
-
Taylor, K.E.1
-
46
-
-
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
-
48
-
-
30444437204
-
Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance
-
Willmott CJ, Matsuura K (2005) Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res 30:79–82. doi:10.3354/cr030079
-
(2005)
Clim Res
, vol.30
, pp. 79-82
-
-
Willmott, C.J.1
Matsuura, K.2
-
50
-
-
79953855364
-
Firefly algorithm, stochastic test functions and design optimization
-
Yang X-S (2010) Firefly algorithm, stochastic test functions and design optimization. Int J Bio-inspired Comput 2(2):78–84. doi:10.1504/IJBIC.2010.032124
-
(2010)
Int J Bio-inspired Comput
, vol.2
, Issue.2
, pp. 78-84
-
-
Yang, X.-S.1
-
51
-
-
84945157492
-
Artificial intelligence based models for stream-flow forecasting: 2000–2015
-
Yaseen ZM, El-shafie A, Jaafar O et al (2015) 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
-
52
-
-
85006356473
-
Non-tuned machine learning approach for hydrological time series forecasting
-
(a)
-
Yaseen ZM, Allawi MF, Yousif AA, Jaafar O, Hamzah FM, El-Shafie A (2016a) Non-tuned machine learning approach for hydrological time series forecasting. Neural Comput & Appl 1–13. doi: 10.1007/s00521-016-2763-0
-
(2016)
Neural Comput & Appl
, pp. 1-13
-
-
Yaseen, Z.M.1
Allawi, M.F.2
Yousif, A.A.3
Jaafar, O.4
Hamzah, F.M.5
El-Shafie, A.6
-
53
-
-
84994591754
-
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
-
et al, (, b
-
Yaseen ZM, Jaafar O, Deo RC et al (2016b) Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq. J Hydrol. doi:10.1016/j.jhydrol.2016.09.035
-
(2016)
J Hydrol
-
-
Yaseen, Z.M.1
Jaafar, O.2
Deo, R.C.3
-
54
-
-
78650179085
-
A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer
-
Yoon H, Jun SC, Hyun Y, Bae GO, & Lee KK (2011) A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer. JHydrol 396(1):128–138
-
(2011)
Jhydrol
, vol.396
, Issue.1
, pp. 128-138
-
-
Yoon, H.1
Jun, S.C.2
Hyun, Y.3
Bae, G.O.4
Lee, K.K.5
|