메뉴 건너뛰기




Volumn 295, Issue 1-4, 2004, Pages 246-262

Improved streamflow forecasting using self-organizing radial basis function artificial neural networks

Author keywords

Cross validation; Neural network; Radial basis function; Self organizing feature map; Streamflow forecasting

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; FORECASTING; HYDROLOGY; RADIAL BASIS FUNCTION NETWORKS; WATER RESOURCES;

EID: 3142538909     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2004.03.027     Document Type: Article
Times cited : (188)

References (38)
  • 4
    • 0034174280 scopus 로고    scopus 로고
    • Committee on the application of anns in hydrology artificial neural networks in hydrology I: Preliminary concepts
    • ASCE Task Committee on the application of ANNs in hydrology. Committee on the application of anns in hydrology artificial neural networks in hydrology I: preliminary concepts. Journal of Hydrologic Engineering. 5:(2):2000;115-123
    • (2000) Journal of Hydrologic Engineering , vol.5 , Issue.2 , pp. 115-123
  • 5
    • 0034174396 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology, II: Hydrologic application
    • ASCE Task Committee on the application of ANNs in hydrology. artificial neural networks in hydrology, II: hydrologic application. Journal of Hydrologic Engineering. 5:(2):2000;124-137
    • (2000) Journal of Hydrologic Engineering , vol.5 , Issue.2 , pp. 124-137
  • 9
    • 0037428019 scopus 로고    scopus 로고
    • Estuary water-stage forecasting by using radial basis function neural network
    • Chang F.J., Chen Y.C. Estuary water-stage forecasting by using radial basis function neural network. Journal of Hydrology. 270:2003;158-166
    • (2003) Journal of Hydrology , vol.270 , pp. 158-166
    • Chang, F.J.1    Chen, Y.C.2
  • 10
    • 0026116468 scopus 로고
    • Orthogonal least squares learning algorithm for radial basis function networks
    • Chen S., Cowan C.F.N., Grant P.M. Orthogonal least squares learning algorithm for radial basis function networks. IEEE Transactions on Neural Networks. 2:(2):1991;302-309
    • (1991) IEEE Transactions on Neural Networks , vol.2 , Issue.2 , pp. 302-309
    • Chen, S.1    Cowan, C.F.N.2    Grant, P.M.3
  • 12
    • 0027294340 scopus 로고
    • Improving model selection by nonconvergent method
    • Finnoff W. Improving model selection by nonconvergent method. Neural Networks. 6:1993;771-783
    • (1993) Neural Networks , vol.6 , pp. 771-783
    • Finnoff, W.1
  • 13
    • 0024991997 scopus 로고
    • Networks and the best approximation property
    • Girosi F., Pogio T. Networks and the best approximation property. Biological Cybernetics. 63:1990;169-176
    • (1990) Biological Cybernetics , vol.63 , pp. 169-176
    • Girosi, F.1    Pogio, T.2
  • 14
    • 0000008790 scopus 로고    scopus 로고
    • Note on fee lunches and cross-validation
    • Goutte C. Note on fee lunches and cross-validation. Neural Computation. 9:1997;1211-1215
    • (1997) Neural Computation , vol.9 , pp. 1211-1215
    • Goutte, C.1
  • 17
    • 0029413797 scopus 로고
    • Artificial neural network modeling of the rainfall-runoff process
    • Hsu K., Gupta H.V., Sorooshian S. Artificial neural network modeling of the rainfall-runoff process. Water Resources Research. 31:(10):1995;2517-2530
    • (1995) Water Resources Research , vol.31 , Issue.10 , pp. 2517-2530
    • Hsu, K.1    Gupta, H.V.2    Sorooshian, S.3
  • 18
    • 0032917913 scopus 로고    scopus 로고
    • Estimation of physical variables from multichannel remotely sensed imagery using a neural network: Application to rainfall estimation
    • Hsu K., Gupta H.V., Gao X., Sorooshian S. Estimation of physical variables from multichannel remotely sensed imagery using a neural network: application to rainfall estimation. Water Resources Research. 35:(5):1999;1605-1618
    • (1999) Water Resources Research , vol.35 , Issue.5 , pp. 1605-1618
    • Hsu, K.1    Gupta, H.V.2    Gao, X.3    Sorooshian, S.4
  • 20
    • 13244251543 scopus 로고    scopus 로고
    • SOLO-An Artificial neural network suitable for hydrologic modeling and analysis
    • see also page 17
    • Hsu K.L., Gupta H.V., Gao X., Sorooshian S., Imam B. SOLO-An Artificial neural network suitable for hydrologic modeling and analysis. Water Resources Research. 38:(12):2002;1-38. see also page 17
    • (2002) Water Resources Research , vol.38 , Issue.12 , pp. 1-38
    • Hsu, K.L.1    Gupta, H.V.2    Gao, X.3    Sorooshian, S.4    Imam, B.5
  • 26
    • 0029748915 scopus 로고    scopus 로고
    • A neural network model of rainfall-runoff using radial basis functions
    • No. 4
    • Mason J.C., Price R.K., Temme A. A neural network model of rainfall-runoff using radial basis functions. Journal of Hydraulic Research. 34:1996;. No. 4
    • (1996) Journal of Hydraulic Research , vol.34
    • Mason, J.C.1    Price, R.K.2    Temme, A.3
  • 28
    • 0000672424 scopus 로고
    • Fast learning in networks of locally tuned processing units
    • Moody J., Darken C.J. Fast learning in networks of locally tuned processing units. Neural Computation. 1:(2):1989;281-294
    • (1989) Neural Computation , vol.1 , Issue.2 , pp. 281-294
    • Moody, J.1    Darken, C.J.2
  • 29
    • 0004399787 scopus 로고
    • Cross-validation estimates IMSE
    • J.D. Cowan, G. Tesauro, & J. Alspector. San Mateo, CA: Morgan Kaufman
    • Plutowski M., Sakata S., White H. Cross-validation estimates IMSE. Cowan J.D., Tesauro G., Alspector J. Advances in Neural Information Processing Systems 6. 6:1994;391-398 Morgan Kaufman, San Mateo, CA
    • (1994) Advances in Neural Information Processing Systems 6 , vol.6 , pp. 391-398
    • Plutowski, M.1    Sakata, S.2    White, H.3
  • 30
    • 0001355838 scopus 로고
    • Radial Basis Function for Multivariable Interpolation: A review
    • J.C. Mason, & M.G. Cox. Clarendon Press: Oxford
    • Powell M.J.D. Radial Basis Function for Multivariable Interpolation: A review. Mason J.C., Cox M.G. Algorithms for Approximation. 1987;143-167 Oxford, Clarendon Press
    • (1987) Algorithms for Approximation , pp. 143-167
    • Powell, M.J.D.1
  • 31
    • 0033167344 scopus 로고    scopus 로고
    • Rainfall-Runoff modeling using artificial neural networks
    • Sezin T.A., Johnson P.A. Rainfall-Runoff modeling using artificial neural networks. Journal of Hydrologic Engineering. 4:(3):1999;232-239
    • (1999) Journal of Hydrologic Engineering , vol.4 , Issue.3 , pp. 232-239
    • Sezin, T.A.1    Johnson, P.A.2
  • 32
    • 0034174397 scopus 로고    scopus 로고
    • Precipitation-Runoff modeling using artificial neural networks and conceptual models
    • Sezin T.A., Masrkus M. Precipitation-Runoff modeling using artificial neural networks and conceptual models. Journal of Hydrologic Engineering. 5:(2):2000;156-161
    • (2000) Journal of Hydrologic Engineering , vol.5 , Issue.2 , pp. 156-161
    • Sezin, T.A.1    Masrkus, M.2
  • 33
    • 0021084897 scopus 로고
    • Evaluation of maximum likelihood parameter estimation techniques for conceptual rainfall-runoff models: Influence of calibration data variability and length on model credibility
    • Sorooshian S., Gupta V.K., Fulton J. Evaluation of maximum likelihood parameter estimation techniques for conceptual rainfall-runoff models: influence of calibration data variability and length on model credibility. Water Resources Research. 19:(1):1983;251-259
    • (1983) Water Resources Research , vol.19 , Issue.1 , pp. 251-259
    • Sorooshian, S.1    Gupta, V.K.2    Fulton, J.3
  • 35
    • 0031898654 scopus 로고    scopus 로고
    • River stage forecasting using artificial neural networks
    • Thirumalaiah K., Deo M.C. River stage forecasting using artificial neural networks. Journal of Hydrologic Engineering. 3:(1):1998;26-32
    • (1998) Journal of Hydrologic Engineering , vol.3 , Issue.1 , pp. 26-32
    • Thirumalaiah, K.1    Deo, M.C.2
  • 37
    • 0018655105 scopus 로고
    • A Dimensionally homogeneous and statistically optimal model for predicting the mean annual flood
    • Wong S.T. A Dimensionally homogeneous and statistically optimal model for predicting the mean annual flood. Journal of Hydrology, Amsterdam. 42:1979;269-279
    • (1979) Journal of Hydrology, Amsterdam , vol.42 , pp. 269-279
    • Wong, S.T.1
  • 38
    • 0030162090 scopus 로고    scopus 로고
    • Automatic calibration of conceptual rainfall-runoff models: Sensitivity to calibration data
    • Yapo P.O., Gupta H.V., Sorooshian S. Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data. Journal of Hydrology. 181:1996;23-48
    • (1996) Journal of Hydrology. , vol.181 , pp. 23-48
    • Yapo, P.O.1    Gupta, H.V.2    Sorooshian, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.