메뉴 건너뛰기




Volumn 5, Issue 4, 2003, Pages 245-258

Data transformation for neural network models in water resources applications

Author keywords

Artificial neural networks; Data transformation; Forecasting; Salinity modelling; Water quality

Indexed keywords


EID: 10644292718     PISSN: 14647141     EISSN: 14651734     Source Type: Journal    
DOI: 10.2166/hydro.2003.0021     Document Type: Article
Times cited : (31)

References (16)
  • 1
    • 0343343722 scopus 로고
    • Algorithm AS 111: The percentage points of the normal distribution
    • Beasley, J. D. & Springer, S. G. 1977 Algorithm AS 111: the percentage points of the normal distribution. Appl. Stat. 26 (1), 118-121.
    • (1977) Appl. Stat. , vol.26 , Issue.1 , pp. 118-121
    • Beasley, J.D.1    Springer, S.G.2
  • 2
    • 0036221122 scopus 로고    scopus 로고
    • Optimal division of data for neural network models in water resources applications
    • (10.1029/2001WR000266)
    • Bowden, G. J., Maier, H. R. & Dandy, G. C. 2002 Optimal division of data for neural network models in water resources applications. Wat. Res. Res. 38 (2), 2-1-2-11 (10.1029/2001WR000266).
    • (2002) Wat. Res. Res. , vol.38 , Issue.2 , pp. 21-211
    • Bowden, G.J.1    Maier, H.R.2    Dandy, G.C.3
  • 3
    • 0025791270 scopus 로고
    • Introduction to artificial neural systems for pattern recognition
    • Burke, L. I. 1991 Introduction to artificial neural systems for pattern recognition. Comput. Oper. Res. 18 (2), 211-220.
    • (1991) Comput. Oper. Res. , vol.18 , Issue.2 , pp. 211-220
    • Burke, L.I.1
  • 4
    • 0024861871 scopus 로고
    • Approximation by superpositions of a sigmoidal function
    • Cybenko, G. 1989 Approximation by superpositions of a sigmoidal function. Math. Control Signals Syst. 2, 203-314.
    • (1989) Math. Control Signals Syst. , vol.2 , pp. 203-314
    • Cybenko, G.1
  • 5
    • 0039988139 scopus 로고    scopus 로고
    • Time series forecasting with neural networks: A comparative study using the airline data
    • Faraway, J. & Chatfield, C. 1998 Time series forecasting with neural networks: a comparative study using the airline data. Appl. Statist. 47 (2), 231-250.
    • (1998) Appl. Statist. , vol.47 , Issue.2 , pp. 231-250
    • Faraway, J.1    Chatfield, C.2
  • 6
    • 0028416331 scopus 로고
    • Neural networks in civil engineering I: Principles and understanding
    • Flood, I. & Kartam, N. 1994 Neural networks in civil engineering. I: Principles and understanding. J. Comput. Civil Engng. 8 (2), 131-148.
    • (1994) J. Comput. Civil Engng. , vol.8 , Issue.2 , pp. 131-148
    • Flood, I.1    Kartam, N.2
  • 7
    • 0001573780 scopus 로고    scopus 로고
    • Comment on 'The use of artificial neural networks for the prediction of water quality parameters' by H
    • Fortin, V., Ouarda, T. B. M. J. & Bobee, B. 1997 Comment on 'The use of artificial neural networks for the prediction of water quality parameters' by H. R. Maier & G. C. Dandy. Wat. Res. Res. 33 (10), 2423-2424.
    • (1997) R. Maier & G. C. Dandy. Wat. Res. Res. , vol.33 , Issue.10 , pp. 2423-2424
    • Fortin, V.1    Ouarda, T.B.M.J.2    Bobee, B.3
  • 9
    • 0029663621 scopus 로고    scopus 로고
    • The use of artificial neural networks for the prediction of water quality parameters
    • Maier, H. R. & Dandy, G. C. 1996 The use of artificial neural networks for the prediction of water quality parameters. Wat. Res. Res. 32 (4), 1013-1022.
    • (1996) Wat. Res. Res. , vol.32 , Issue.4 , pp. 1013-1022
    • Maier, H.R.1    Dandy, G.C.2
  • 10
    • 0032051569 scopus 로고    scopus 로고
    • The effect of internal parameters and geometry on the performance of back-propagation neural networks: An empirical study
    • Maier, H. R. & Dandy, G. C. 1998 The effect of internal parameters and geometry on the performance of back-propagation neural networks: an empirical study. Environ. Modell. Software 13, 193-209.
    • (1998) Environ. Modell. Software , vol.13 , pp. 193-209
    • Maier, H.R.1    Dandy, G.C.2
  • 11
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for the prediction and forecasting of water resources variables: A review of modelling issues and applications
    • Maier, H. R. & Dandy, G. C. 2000 Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications. Environ. Modell. Software 15, 101-124.
    • (2000) Environ. Modell. Software , vol.15 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 16
    • 0034171993 scopus 로고    scopus 로고
    • Reducing prediction error by transforming input data for neural networks
    • Shi, J. J. 2000 Reducing prediction error by transforming input data for neural networks. J. Comput. Civil Engng. 14 (2), 109-116.
    • (2000) J. Comput. Civil Engng. , vol.14 , Issue.2 , pp. 109-116
    • Shi, J.J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.