-
1
-
-
33750953806
-
Water allocation improvement in river basin using adaptive neural fuzzy reinforcement learning approach
-
Abolpour B., Javan M., Karamouz M. Water allocation improvement in river basin using adaptive neural fuzzy reinforcement learning approach. Applied Soft Computing Journal 2007, 7:265-285.
-
(2007)
Applied Soft Computing Journal
, vol.7
, pp. 265-285
-
-
Abolpour, B.1
Javan, M.2
Karamouz, M.3
-
2
-
-
34249794005
-
Timing error correction procedure applied to neural network rainfall-runoff modelling
-
Abrahart R.J., Heppenstall A.J., See L.M. Timing error correction procedure applied to neural network rainfall-runoff modelling. Hydrological Sciences Journal 2007, 52:414-431.
-
(2007)
Hydrological Sciences Journal
, vol.52
, pp. 414-431
-
-
Abrahart, R.J.1
Heppenstall, A.J.2
See, L.M.3
-
3
-
-
0016355478
-
New look at the statistical model identification
-
AC
-
Akaike H. New look at the statistical model identification. IEEE Transactions on Automatic Control 1974, AC-19:716-723.
-
(1974)
IEEE Transactions on Automatic Control
, vol.19
, pp. 716-723
-
-
Akaike, H.1
-
4
-
-
14544280631
-
RSPOP: rough set-based pseudo outer-product fuzzy rule identification algorithm
-
Ang K.K., Quek C. RSPOP: rough set-based pseudo outer-product fuzzy rule identification algorithm. Neural Computation 2005, 17:205-243.
-
(2005)
Neural Computation
, vol.17
, pp. 205-243
-
-
Ang, K.K.1
Quek, C.2
-
5
-
-
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. A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff. Journal of Hydrology 2007, 337:22-34.
-
(2007)
Journal of Hydrology
, vol.337
, pp. 22-34
-
-
Aqil, M.1
Kita, I.2
Yano, A.3
Nishiyama, S.4
-
6
-
-
28444489651
-
Adaptive neuro-fuzzy inference system for prediction of water level in reservoir
-
Chang F.J., Chang Y.T. Adaptive neuro-fuzzy inference system for prediction of water level in reservoir. Advances in Water Resources 2006, 29:1-10.
-
(2006)
Advances in Water Resources
, vol.29
, pp. 1-10
-
-
Chang, F.J.1
Chang, Y.T.2
-
7
-
-
0035340711
-
A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction
-
Chang F.J., Chen Y.C. A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction. Journal of Hydrology 2001, 245:153-164.
-
(2001)
Journal of Hydrology
, vol.245
, pp. 153-164
-
-
Chang, F.J.1
Chen, Y.C.2
-
8
-
-
33646075449
-
The strategy of building a flood forecast model by neuro-fuzzy network
-
Chen S.H., Lin Y.H., Chang L.C., Chang F.J. The strategy of building a flood forecast model by neuro-fuzzy network. Hydrological Processes 2006, 20:1525-1540.
-
(2006)
Hydrological Processes
, vol.20
, pp. 1525-1540
-
-
Chen, S.H.1
Lin, Y.H.2
Chang, L.C.3
Chang, F.J.4
-
9
-
-
58849091317
-
HebbR2-taffic: a novel application of neuro-fuzzy network for visual based traffic monitoring system
-
Cho S.Y., Quek C., Seah S.X., Chong C.H. HebbR2-taffic: a novel application of neuro-fuzzy network for visual based traffic monitoring system. Expert Systems with Applications 2009, 36:6343-6356.
-
(2009)
Expert Systems with Applications
, vol.36
, pp. 6343-6356
-
-
Cho, S.Y.1
Quek, C.2
Seah, S.X.3
Chong, C.H.4
-
10
-
-
47049118310
-
Comparison between kinematic wave and artificial neural network models in event-based runoff simulation for an overland plane
-
Chua L.H.C., Wong T.S.W., Sriramula L.K. Comparison between kinematic wave and artificial neural network models in event-based runoff simulation for an overland plane. Journal of Hydrology 2008, 357:337-348.
-
(2008)
Journal of Hydrology
, vol.357
, pp. 337-348
-
-
Chua, L.H.C.1
Wong, T.S.W.2
Sriramula, L.K.3
-
11
-
-
0032005702
-
An artificial neural network approach to rainfall-runoff modelling
-
Dawson C.W., Wilby R. An artificial neural network approach to rainfall-runoff modelling. Hydrological Sciences Journal 1998, 43:47-66.
-
(1998)
Hydrological Sciences Journal
, vol.43
, pp. 47-66
-
-
Dawson, C.W.1
Wilby, R.2
-
12
-
-
0033512986
-
A comparison of artificial neural networks used for river flow forecasting
-
Dawson C.W., Wilby R.L. A comparison of artificial neural networks used for river flow forecasting. Hydrology and Earth System Sciences 1999, 3:529-540.
-
(1999)
Hydrology and Earth System Sciences
, vol.3
, pp. 529-540
-
-
Dawson, C.W.1
Wilby, R.L.2
-
13
-
-
23744444467
-
Constraints of artificial neural networks for rainfall-runoff modelling: trade-offs in hydrological state representation and model evaluation
-
de Vos N.J., Rientjes T.H.M. Constraints of artificial neural networks for rainfall-runoff modelling: trade-offs in hydrological state representation and model evaluation. Hydrology and Earth System Sciences 2005, 9:111-126.
-
(2005)
Hydrology and Earth System Sciences
, vol.9
, pp. 111-126
-
-
de Vos, N.J.1
Rientjes, T.H.M.2
-
14
-
-
0031998129
-
Application example of neural networks for time series analysis: rainfall-runoff modeling
-
Furundzic D. Application example of neural networks for time series analysis: rainfall-runoff modeling. Signal Processing 1998, 64:383-396.
-
(1998)
Signal Processing
, vol.64
, pp. 383-396
-
-
Furundzic, D.1
-
15
-
-
0029413797
-
Artificial neural network modeling of the rainfall-runoff process
-
Hsu K.-L., Gupta H.V., Sorooshian S. Artificial neural network modeling of the rainfall-runoff process. Water Resources Research 1995, 31:2517-2530.
-
(1995)
Water Resources Research
, vol.31
, pp. 2517-2530
-
-
Hsu, K.-L.1
Gupta, H.V.2
Sorooshian, S.3
-
16
-
-
1542287371
-
Identification of physical processes inherent in artificial neural network rainfall runoff models
-
Jain A., Sudheer K.P., Srinivasulu S. Identification of physical processes inherent in artificial neural network rainfall runoff models. Hydrological Processes 2004, 18:571-581.
-
(2004)
Hydrological Processes
, vol.18
, pp. 571-581
-
-
Jain, A.1
Sudheer, K.P.2
Srinivasulu, S.3
-
19
-
-
0003472427
-
-
Prentice-Hall Inc., Upper Saddle River, NJ, USA
-
Lin C.T., Lee C.S.G. Neural Fuzzy Systems: A Neuro-fuzzy Synergism to Intelligent Systems 1996, Prentice-Hall Inc., Upper Saddle River, NJ, USA.
-
(1996)
Neural Fuzzy Systems: A Neuro-fuzzy Synergism to Intelligent Systems
-
-
Lin, C.T.1
Lee, C.S.G.2
-
20
-
-
0032301756
-
Predicting a chaotic time series using a fuzzy neural network
-
Maguire L.P., Roche B., McGinnity T.M., McDaid L.J. Predicting a chaotic time series using a fuzzy neural network. Information Sciences 1998, 112:125-136.
-
(1998)
Information Sciences
, vol.112
, pp. 125-136
-
-
Maguire, L.P.1
Roche, B.2
McGinnity, T.M.3
McDaid, L.J.4
-
22
-
-
0034187785
-
Neuro-fuzzy rule generation: survey in soft computing framework
-
Mitra S., Hayashi Y. Neuro-fuzzy rule generation: survey in soft computing framework. IEEE Transactions on Neural Networks 2000, 11:748-768.
-
(2000)
IEEE Transactions on Neural Networks
, vol.11
, pp. 748-768
-
-
Mitra, S.1
Hayashi, Y.2
-
23
-
-
66249107437
-
Flood forecasting using ANN, neuro-fuzzy, and neuro-GA models
-
Mukerji A., Chatterjee C., Singh Raghuwanshi N. Flood forecasting using ANN, neuro-fuzzy, and neuro-GA models. Journal of Hydrologic Engineering 2009, 14:647-652.
-
(2009)
Journal of Hydrologic Engineering
, vol.14
, pp. 647-652
-
-
Mukerji, A.1
Chatterjee, C.2
Singh Raghuwanshi, N.3
-
24
-
-
0014776873
-
River flow forecasting through conceptual models. Part I - A discussion of principles
-
Nash J.E., Sutcliffe J.V. River flow forecasting through conceptual models. Part I - A discussion of principles. Journal of Hydrology 1970, 10:282-290.
-
(1970)
Journal of Hydrology
, vol.10
, pp. 282-290
-
-
Nash, J.E.1
Sutcliffe, J.V.2
-
25
-
-
1942490118
-
A neuro-fuzzy computing technique for modeling hydrological time series
-
Nayak P.C., Sudheer K.P., Rangan D.M., Ramasastri K.S. A neuro-fuzzy computing technique for modeling hydrological time series. Journal of Hydrology 2004, 291:52-66.
-
(2004)
Journal of Hydrology
, vol.291
, pp. 52-66
-
-
Nayak, P.C.1
Sudheer, K.P.2
Rangan, D.M.3
Ramasastri, K.S.4
-
26
-
-
14844352523
-
Fuzzy computing based rainfall-runoff model for real time flood forecasting
-
Nayak P.C., Sudheer K.P., Ramasastri K.S. Fuzzy computing based rainfall-runoff model for real time flood forecasting. Hydrological Processes 2005, 19:955-968.
-
(2005)
Hydrological Processes
, vol.19
, pp. 955-968
-
-
Nayak, P.C.1
Sudheer, K.P.2
Ramasastri, K.S.3
-
29
-
-
31744432525
-
FITSK: online local learning with generic fuzzy input Takagi-Sugeno-Kang fuzzy framework for nonlinear system estimation
-
Quah K.H., Quek C. FITSK: online local learning with generic fuzzy input Takagi-Sugeno-Kang fuzzy framework for nonlinear system estimation. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 2006, 36:166-178.
-
(2006)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
, vol.36
, pp. 166-178
-
-
Quah, K.H.1
Quek, C.2
-
31
-
-
4644296256
-
Predicting catchment flow in a semi-arid region via an artificial neural network technique
-
Riad S., Mania J., Bouchaou L., Najjar Y. Predicting catchment flow in a semi-arid region via an artificial neural network technique. Hydrological Processes 2004, 18:2387-2393.
-
(2004)
Hydrological Processes
, vol.18
, pp. 2387-2393
-
-
Riad, S.1
Mania, J.2
Bouchaou, L.3
Najjar, Y.4
-
32
-
-
0018015137
-
Modeling by shortest data description
-
Rissanen J. Modeling by shortest data description. Automatica 1978, 14:465-471.
-
(1978)
Automatica
, vol.14
, pp. 465-471
-
-
Rissanen, J.1
-
33
-
-
34047254142
-
Suitability of different neural networks in daily flow forecasting
-
Singh P., Deo M.C. Suitability of different neural networks in daily flow forecasting. Applied Soft Computing Journal 2007, 7:968-978.
-
(2007)
Applied Soft Computing Journal
, vol.7
, pp. 968-978
-
-
Singh, P.1
Deo, M.C.2
-
34
-
-
37549060590
-
Runoff analysis for a small watershed of tono area Japan by back propagation artificial neural network with seasonal data
-
Sohail A., Watanabe K., Takeuchi S. Runoff analysis for a small watershed of tono area Japan by back propagation artificial neural network with seasonal data. Water Resources Management 2008, 22:1-22.
-
(2008)
Water Resources Management
, vol.22
, pp. 1-22
-
-
Sohail, A.1
Watanabe, K.2
Takeuchi, S.3
-
35
-
-
0021892282
-
Fuzzy identification of systems and its applications to modeling and control
-
Takagi T., Sugeno M. Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems, Man and Cybernetics 1985, 15:116-132.
-
(1985)
IEEE Transactions on Systems, Man and Cybernetics
, vol.15
, pp. 116-132
-
-
Takagi, T.1
Sugeno, M.2
-
36
-
-
33751081243
-
ANN and fuzzy logic models for simulating event-based rainfall-runoff
-
Tayfur G., Singh V.P. ANN and fuzzy logic models for simulating event-based rainfall-runoff. Journal of Hydraulic Engineering 2006, 132:1321-1330.
-
(2006)
Journal of Hydraulic Engineering
, vol.132
, pp. 1321-1330
-
-
Tayfur, G.1
Singh, V.P.2
-
37
-
-
0034174397
-
Precipitation-runoff modeling using artificial neural networks and conceptual models
-
Tokar A.S., Markus M. Precipitation-runoff modeling using artificial neural networks and conceptual models. Journal of Hydrologic Engineering 2000, 5:156-161.
-
(2000)
Journal of Hydrologic Engineering
, vol.5
, pp. 156-161
-
-
Tokar, A.S.1
Markus, M.2
-
38
-
-
0026711368
-
Improving the convergence of the back-propagation algorithm
-
Van Ooyen A., Nienhuis B. Improving the convergence of the back-propagation algorithm. Neural Networks 1992, 5:465-471.
-
(1992)
Neural Networks
, vol.5
, pp. 465-471
-
-
Van Ooyen, A.1
Nienhuis, B.2
-
39
-
-
11144347859
-
Comparison of data-driven Takagi-Sugeno models of rainfall-discharge dynamics
-
Vernieuwe H., Georgieva O., De Baets B., Pauwels V.R.N., Verhoest N.E.C., De Troch F.P. Comparison of data-driven Takagi-Sugeno models of rainfall-discharge dynamics. Journal of Hydrology 2005, 302:173-186.
-
(2005)
Journal of Hydrology
, vol.302
, pp. 173-186
-
-
Vernieuwe, H.1
Georgieva, O.2
De Baets, B.3
Pauwels, V.R.N.4
Verhoest, N.E.C.5
De Troch, F.P.6
-
40
-
-
54249137704
-
Optimum rainfall interval and manning's roughness coefficient for runoff simulation
-
Wong T.S.W. Optimum rainfall interval and manning's roughness coefficient for runoff simulation. Journal of Hydrologic Engineering 2008, 13:1097-1102.
-
(2008)
Journal of Hydrologic Engineering
, vol.13
, pp. 1097-1102
-
-
Wong, T.S.W.1
-
41
-
-
58849094959
-
Modelling level change in lakes using neuro-fuzzy and artificial neural networks
-
Yarar A., Onucyildiz M., Copty N.K. Modelling level change in lakes using neuro-fuzzy and artificial neural networks. Journal of Hydrology 2009, 365:329-334.
-
(2009)
Journal of Hydrology
, vol.365
, pp. 329-334
-
-
Yarar, A.1
Onucyildiz, M.2
Copty, N.K.3
-
42
-
-
45849090754
-
Application of artificial intelligence models in water quality forecasting
-
Yeon I.S., Kim J.H., Jun K.W. Application of artificial intelligence models in water quality forecasting. Environmental Technology 2008, 29:625-631.
-
(2008)
Environmental Technology
, vol.29
, pp. 625-631
-
-
Yeon, I.S.1
Kim, J.H.2
Jun, K.W.3
-
43
-
-
58849164849
-
Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: an application to Izmir, Turkey
-
Yurdusev M.A., Firat M. Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: an application to Izmir, Turkey. Journal of Hydrology 2009, 365:225-234.
-
(2009)
Journal of Hydrology
, vol.365
, pp. 225-234
-
-
Yurdusev, M.A.1
Firat, M.2
|