메뉴 건너뛰기




Volumn 3, Issue 4, 1999, Pages 529-540

A comparison of artificial neural networks used for river flow forecasting

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; FORECASTING METHOD; RAINFALL-RUNOFF MODELING; RIVER FLOW;

EID: 0033512986     PISSN: 10275606     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (75)

References (32)
  • 1
    • 0002484567 scopus 로고    scopus 로고
    • Exploring Neural Network Rainfall-Runoff Modelling
    • Salford University
    • Abrahart, R.J. and Kneale, P.E., 1997. Exploring Neural Network Rainfall-Runoff Modelling, 6th National Hydrology Symposium, Salford University, 9.35-9.44.
    • (1997) 6th National Hydrology Symposium , pp. 935-944
    • Abrahart, R.J.1    Kneale, P.E.2
  • 2
    • 0001024110 scopus 로고
    • First- And second-order methods for learning: Between steepest descent and Newton's method
    • Battiti, R., 1992. First-and second-order methods for learning: between steepest descent and Newton's method, Neural Computation, 4, 141-166.
    • (1992) Neural Computation , vol.4 , pp. 141-166
    • Battiti, R.1
  • 4
    • 0031851620 scopus 로고    scopus 로고
    • Feed-forward artificial neural network model for forecasting rainfall run-off
    • Braddock, R.D., Kremmer, M.L. and Sanzogni, L., 1998. Feed-forward artificial neural network model for forecasting rainfall run-off, Environmetrics, 9, 419-432.
    • (1998) Environmetrics , vol.9 , pp. 419-432
    • Braddock, R.D.1    Kremmer, M.L.2    Sanzogni, L.3
  • 5
    • 0032688155 scopus 로고    scopus 로고
    • River flood forecasting with a neural network model
    • Campolo, M., Andreussi, P. and Soldati, A., 1999. River flood forecasting with a neural network model, Wat. Resour. Res., 35, 1191-1197.
    • (1999) Wat. Resour. Res. , vol.35 , pp. 1191-1197
    • Campolo, M.1    Andreussi, P.2    Soldati, A.3
  • 6
    • 0031277503 scopus 로고    scopus 로고
    • Effects of learning parameters on learning procedure and performance of a BPNN
    • Dai, H. and MacBeth, C., 1997. Effects of learning parameters on learning procedure and performance of a BPNN, Neural Networks, 10, 1505-1521.
    • (1997) Neural Networks , vol.10 , pp. 1505-1521
    • Dai, H.1    MacBeth, C.2
  • 7
    • 0002472406 scopus 로고    scopus 로고
    • A Neural Network Approach to Software Project Effort Estimation
    • Dawson, C.W., 1996. A Neural Network Approach to Software Project Effort Estimation, App. Artificial Intelligence in Eng., 1, 229-237.
    • (1996) App. Artificial Intelligence in Eng. , vol.1 , pp. 229-237
    • Dawson, C.W.1
  • 8
    • 0032005702 scopus 로고    scopus 로고
    • An Artificial Neural Network Approach to Rainfall-Runoff Modelling
    • Dawson, C.W. and Wilby, R., 1998. An Artificial Neural Network Approach To Rainfall-Runoff Modelling, Hydrol. Sci. J., 43, 47-66.
    • (1998) Hydrol. Sci. J. , vol.43 , pp. 47-66
    • Dawson, C.W.1    Wilby, R.2
  • 9
    • 0032123339 scopus 로고    scopus 로고
    • Runoff forecasting using RBF networks with OLS algorithm
    • Fernando, D.A.K. and Jayawardena, A.W., 1998. Runoff forecasting using RBF networks with OLS algorithm, J. Hydrol. Eng., 3, 203-209.
    • (1998) J. Hydrol. Eng. , vol.3 , pp. 203-209
    • Fernando, D.A.K.1    Jayawardena, A.W.2
  • 10
    • 0031998129 scopus 로고    scopus 로고
    • Application of neural networks for time series analysis: Rainfall-runoff modeling
    • Furundzic, D., 1998. Application of neural networks for time series analysis: rainfall-runoff modeling, Signal Processing, 64, 383-396.
    • (1998) Signal Processing , vol.64 , pp. 383-396
    • Furundzic, D.1
  • 12
    • 0001795638 scopus 로고
    • Rainfall-Runoff Modelling as a Problem in Artificial Intelligence: Experience with a Neural Network
    • Cardiff
    • Hall, M.J. and Minns, A.W., 1993. Rainfall-Runoff Modelling as a Problem in Artificial Intelligence: Experience with a Neural Network, BHS 4th National Hydrology Symposium, Cardiff, 5.51-5.57.
    • (1993) BHS 4th National Hydrology Symposium , pp. 551-557
    • Hall, M.J.1    Minns, A.W.2
  • 14
    • 0025964567 scopus 로고
    • Back-propogation algorithm which varies the number of hidden units
    • Hirose, Y., Yamashita, K. and Hijiya, S., 1991. Back-propogation algorithm which varies the number of hidden units, Neural Networks, 4, 61-66.
    • (1991) Neural Networks , vol.4 , pp. 61-66
    • Hirose, Y.1    Yamashita, K.2    Hijiya, S.3
  • 15
    • 0029413797 scopus 로고
    • Artificial Neural Network Modeling of the Rainfall-Runoff Process
    • Hsu, K., Gupta, H.V. and Sorooshian, S., 1995. Artificial Neural Network Modeling of the Rainfall-Runoff Process, Wat. Resour. Res., 31, 2517-2530.
    • (1995) Wat. Resour. Res. , vol.31 , pp. 2517-2530
    • Hsu, K.1    Gupta, H.V.2    Sorooshian, S.3
  • 16
    • 0032030147 scopus 로고    scopus 로고
    • Use of Radial Basis Function Type Artificial Neural Networks for Runoff Simulation
    • Jayawardena, A.W., Achela, D. and Fernando, K., 1998. Use of Radial Basis Function Type Artificial Neural Networks for Runoff Simulation, Computer-aided Civ. Infrastr. Eng., 13, 91-99.
    • (1998) Computer-aided Civ. Infrastr. Eng. , vol.13 , pp. 91-99
    • Jayawardena, A.W.1    Achela, D.2    Fernando, K.3
  • 19
    • 0000759858 scopus 로고
    • Forecasting local weather by means of model output statistics
    • Klein, W.H. and Glahn, H.R., 1974. Forecasting local weather by means of model output statistics, Bull. Am. Meteorol. Soc., 55, 1217-1227.
    • (1974) Bull. Am. Meteorol. Soc. , vol.55 , pp. 1217-1227
    • Klein, W.H.1    Glahn, H.R.2
  • 20
    • 0032920124 scopus 로고    scopus 로고
    • Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation
    • Legates, D.R. and McCabe, G.J., 1999. Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation, Wat. Resour. Res., 35, 233-241.
    • (1999) Wat. Resour. Res. , vol.35 , pp. 233-241
    • Legates, D.R.1    McCabe, G.J.2
  • 21
    • 0031028741 scopus 로고    scopus 로고
    • Effective backpropagation training with variable stepsize
    • Magoulas, G.D., Vrahatis, M.N. and Androulakis, G.S., 1997. Effective backpropagation training with variable stepsize, Neural Networks, 10, 69-82.
    • (1997) Neural Networks , vol.10 , pp. 69-82
    • Magoulas, G.D.1    Vrahatis, M.N.2    Androulakis, G.S.3
  • 22
    • 0029748915 scopus 로고    scopus 로고
    • A Neural Network Model of Rainfall-Runoff Using Radial Basis Functions
    • Mason, J.C., Tem'me, A. and Price, R.K., 1996. A Neural Network Model of Rainfall-Runoff Using Radial Basis Functions, J. Hydraul. Res., 34, 537-548.
    • (1996) J. Hydraul. Res. , vol.34 , pp. 537-548
    • Mason, J.C.1    Tem'me, A.2    Price, R.K.3
  • 24
    • 0037918575 scopus 로고    scopus 로고
    • Living with the Ultimate Black Box: More on Artificial Neural Networks
    • Salford University
    • Minns, A.W. and Hall, M.J., 1997. Living with the Ultimate Black Box: More on Artificial Neural Networks, 6th National Hydrology Symposium, Salford University, 9.45-9.49.
    • (1997) 6th National Hydrology Symposium , pp. 945-949
    • Minns, A.W.1    Hall, M.J.2
  • 25
    • 0031272644 scopus 로고    scopus 로고
    • Neural networks in financial engineering: A study in methodology
    • Refenes, A., Burgess, A.N. and Bents, Y., 1997. Neural networks in financial engineering: a study in methodology, IEEE Trans. Neural Networks, 8, 1223-1267.
    • (1997) IEEE Trans. Neural Networks , vol.8 , pp. 1223-1267
    • Refenes, A.1    Burgess, A.N.2    Bents, Y.3
  • 28
    • 0342506462 scopus 로고    scopus 로고
    • Application of a neural network technique to rainfall-runoff modelling
    • Shamseldin, A.Y., 1997. Application of a neural network technique to rainfall-runoff modelling', J. Hydrol., 199, 272-294.
    • (1997) J. Hydrol. , vol.199 , pp. 272-294
    • Shamseldin, A.Y.1
  • 30
    • 0031898654 scopus 로고    scopus 로고
    • River stage forecasting using artificial neural networks
    • Thirumalaiah, K. and Deo, M.C., 1998. River stage forecasting using artificial neural networks, J. Hydrol. Eng., 3, 26-32.
    • (1998) J. Hydrol. Eng. , vol.3 , pp. 26-32
    • Thirumalaiah, K.1    Deo, M.C.2
  • 31
    • 0013265687 scopus 로고    scopus 로고
    • Streamflow changes in the Sierra Nevada, California, simulated using a statically downscaled General Circulation Model scenario of climate change
    • McLaren, S. and Kniveton, D. (Eds.) Kluwer Academic Publishers, Lancaster, UK, in press
    • Wilby, R.L. and Dettinger, M.D., 1999. Streamflow changes in the Sierra Nevada, California, simulated using a statically downscaled General Circulation Model scenario of climate change, In: McLaren, S. and Kniveton, D. (Eds.) Linking Climate Change to Land Surface Change, Kluwer Academic Publishers, Lancaster, UK, in press.
    • (1999) Linking Climate Change to Land Surface Change
    • Wilby, R.L.1    Dettinger, M.D.2
  • 32
    • 0033019602 scopus 로고    scopus 로고
    • Short term streamflow forecasting using artificial neural networks
    • Zealand, C., M. Burn, D.H. and Simonovic, S.P., 1999. Short term streamflow forecasting using artificial neural networks, J. Hydrol., 214, 32-18.
    • (1999) J. Hydrol. , vol.214 , pp. 32-118
    • Zealand, C.M.1    Burn, D.H.2    Simonovic, S.P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.