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Volumn 18, Issue 13, 2004, Pages 2387-2393

Predicting catchment flow in a semi-arid region via an artificial neural network technique

Author keywords

Artificial neural network; Catchment; Morocco; Prediction flow; Rainfall runoff; Semi arid region; Time series

Indexed keywords

MATHEMATICAL MODELS; NEURAL NETWORKS; RAIN; REGRESSION ANALYSIS; RUNOFF; STREAM FLOW; VEGETATION;

EID: 4644296256     PISSN: 08856087     EISSN: None     Source Type: Journal    
DOI: 10.1002/hyp.1469     Document Type: Article
Times cited : (67)

References (32)
  • 1
    • 0034174280 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology - I: Preliminary concepts
    • ASCE Task Committee
    • ASCE Task Committee. 2000a. Artificial neural networks in hydrology-I: preliminary concepts. Journal of Hydrologic Engineering, American Society of Civil Engineers 5(2): 115-123.
    • (2000) Journal of Hydrologic Engineering, American Society of Civil Engineers , vol.5 , Issue.2 , pp. 115-123
  • 2
    • 0034174396 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology - II: Hydrologic applications
    • ASCE Task Committee
    • ASCE Task Committee. 2000b. Artificial neural networks in hydrology-II: hydrologic applications. Journal of Hydrologic Engineering, American Society of Civil Engineers 5(2): 124-137.
    • (2000) Journal of Hydrologic Engineering, American Society of Civil Engineers , vol.5 , Issue.2 , pp. 124-137
  • 3
    • 0001463667 scopus 로고    scopus 로고
    • A study of the artificial neural network for rainfall-runoff process
    • In Chinese
    • Chang F-J, Suen J-P. 1997. A study of the artificial neural network for rainfall-runoff process. Journal of Chinese Agricultural Engineering 43(1): 9-25. (In Chinese.)
    • (1997) Journal of Chinese Agricultural Engineering , vol.43 , Issue.1 , pp. 9-25
    • Chang, F.-J.1    Suen, J.-P.2
  • 4
    • 0035864789 scopus 로고    scopus 로고
    • Counterpropagation fuzzy neural network for stream-flow reconstruction
    • Chang FJ, Hu HF, Chen YC. 2001. Counterpropagation fuzzy neural network for stream-flow reconstruction. Hydrological Processes 15(2): 219-232.
    • (2001) Hydrological Processes , vol.15 , Issue.2 , pp. 219-232
    • Chang, F.J.1    Hu, H.F.2    Chen, Y.C.3
  • 5
    • 0032829433 scopus 로고    scopus 로고
    • Prévision hydrologique par réseaux de neurones artificiels: état de l'art
    • Coulibaly P, Anctil F, Bobée B. 1999. Prévision hydrologique par réseaux de neurones artificiels: état de l'art. Revue canadienne de génie civil 26(3): 293-304.
    • (1999) Revue Canadienne de Génie Civil , vol.26 , Issue.3 , pp. 293-304
    • Coulibaly, P.1    Anctil, F.2    Bobée, B.3
  • 6
    • 0034621379 scopus 로고    scopus 로고
    • Daily reservoir inflow forecasting using artificial neural networks with stopped training approach
    • Coulibaly P, Anctil F, Bobée B. 2000. Daily reservoir inflow forecasting using artificial neural networks with stopped training approach. Journal of Hydrology 230: 244-257.
    • (2000) Journal of Hydrology , vol.230 , pp. 244-257
    • Coulibaly, P.1    Anctil, F.2    Bobée, B.3
  • 7
    • 0032005702 scopus 로고    scopus 로고
    • An artificial neural network approach to rainfall-runoff modelling
    • Dawson CW, Wilby RL. 1998. An artificial neural network approach to rainfall-runoff modelling. Hydrological Sciences Journal 43: 47-66.
    • (1998) Hydrological Sciences Journal , vol.43 , pp. 47-66
    • Dawson, C.W.1    Wilby, R.L.2
  • 8
    • 0034749335 scopus 로고    scopus 로고
    • Hydrological modelling using artificial neural networks
    • Dawson CW, Wilby RL. 2001. Hydrological modelling using artificial neural networks. Progress in Physical Geography 25: 80-108.
    • (2001) Progress in Physical Geography , vol.25 , pp. 80-108
    • Dawson, C.W.1    Wilby, R.L.2
  • 9
    • 0029673615 scopus 로고    scopus 로고
    • Modélisation de la relation pluie-débit par les réseaux connexionnistes et le filtre de Kalman
    • Dimopoulos I, Lek S, Lauga J. 1996. Modélisation de la relation pluie-débit par les réseaux connexionnistes et le filtre de Kalman. Journal des sciences hydrologiques 42(2): 179-193.
    • (1996) Journal des Sciences Hydrologiques , vol.42 , Issue.2 , pp. 179-193
    • Dimopoulos, I.1    Lek, S.2    Lauga, J.3
  • 11
    • 0027149406 scopus 로고
    • Predicting runoff from rainfall using neural networks
    • Kuo CY (ed.). Proceedings of the Symposium Sponsored by the Hydraulics Division of ASCE: San Francisco, CA, 25-30 July 1993 American Society of Civil Engineers: New York
    • Halff AH, Halff HM, Azmoodeh M. 1993. Predicting runoff from rainfall using neural networks. In Engineering Hydrology, Kuo CY (ed.). Proceedings of the Symposium Sponsored by the Hydraulics Division of ASCE: San Francisco, CA, 25-30 July 1993 American Society of Civil Engineers: New York; 760-765.
    • (1993) Engineering Hydrology , pp. 760-765
    • Halff, A.H.1    Halff, H.M.2    Azmoodeh, M.3
  • 13
    • 0029413797 scopus 로고
    • Artificial neural network modeling of the rainfall-runoff process
    • Hsu KL, Gupta HV, Sorooshian S. 1995. Artificial neural network modeling of the rainfall-runoff process. Water Resources Research 31(10): 2517-2530.
    • (1995) Water Resources Research , vol.31 , Issue.10 , pp. 2517-2530
    • Hsu, K.L.1    Gupta, H.V.2    Sorooshian, S.3
  • 14
    • 0035472003 scopus 로고    scopus 로고
    • River flow time series prediction with a range-dependent neural network
    • Hu TS, Lam KC, Ng ST. 2001. River flow time series prediction with a range-dependent neural network. Hydrological Science Journal 46(5): 729-745.
    • (2001) Hydrological Science Journal , vol.46 , Issue.5 , pp. 729-745
    • Hu, T.S.1    Lam, K.C.2    Ng, S.T.3
  • 15
    • 0034641121 scopus 로고    scopus 로고
    • River flow prediction using artificial neural networks: Generalisation beyond the calibration range
    • Imrie CE, Durucan S, Korre A. 2000. River flow prediction using artificial neural networks: generalisation beyond the calibration range. Journal of Hydrology 233(1-4): 138-153.
    • (2000) Journal of Hydrology , vol.233 , Issue.1-4 , pp. 138-153
    • Imrie, C.E.1    Durucan, S.2    Korre, A.3
  • 17
    • 0030430689 scopus 로고    scopus 로고
    • Modélisation de la relation pluie- débit à l'aide des réseaux de neurones artificials
    • Lek S, Dimopoulos I, Derraz M, El Ghachtoul Y. 1996. Modélisation de la relation pluie- débit à l'aide des réseaux de neurones artificials. Revue des Sciences de l'eau 9(3): 319-331.
    • (1996) Revue des Sciences de L'eau , vol.9 , Issue.3 , pp. 319-331
    • Lek, S.1    Dimopoulos, I.2    Derraz, M.3    El Ghachtoul, Y.4
  • 18
    • 0023331258 scopus 로고
    • An introduction to computing with neural nets
    • April
    • Lippmann RP. 1987. An introduction to computing with neural nets. IEEE ASSP Magazine April: 4-22.
    • (1987) IEEE ASSP Magazine , pp. 4-22
    • Lippmann, R.P.1
  • 19
    • 0029413502 scopus 로고
    • Neural nets for modelling rainfall-runoff transformations
    • Lorrai M, Sechi GM. 1995. Neural nets for modelling rainfall-runoff transformations. Water Resources Management 9: 299-313.
    • (1995) Water Resources Management , vol.9 , pp. 299-313
    • Lorrai, M.1    Sechi, G.M.2
  • 20
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for the prediction and forecasting of water resources variables: A review of modeling issues and application
    • Maier HR, Dandy GC. 2000. Neural networks for the prediction and forecasting of water resources variables: a review of modeling issues and application. Environmental Modeling and Software 15: 101-124.
    • (2000) Environmental Modeling and Software , vol.15 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 21
    • 0030159380 scopus 로고    scopus 로고
    • Artificial neural networks as rainfall-runoff models
    • Minns AW, Hall MJ. 1996. Artificial neural networks as rainfall-runoff models. Hydrological Sciences Journal 41(3): 399-418.
    • (1996) Hydrological Sciences Journal , vol.41 , Issue.3 , pp. 399-418
    • Minns, A.W.1    Hall, M.J.2
  • 25
    • 0030240007 scopus 로고    scopus 로고
    • Utilizing computational neural networks for evaluating the permeability of compacted clay liners
    • Najjar Y, Basheer, Imad A. 1996. Utilizing computational neural networks for evaluating the permeability of compacted clay liners. Geotechnical and Geological Engineering 14(3): 193-212.
    • (1996) Geotechnical and Geological Engineering , vol.14 , Issue.3 , pp. 193-212
    • Najjar, Y.1    Basheer Imad, A.2
  • 27
    • 0033535432 scopus 로고    scopus 로고
    • A non-linear rainfall-runoff model using an artificial neural network
    • Sajikumar N, Thandaveswara BS. 1999. A non-linear rainfall-runoff model using an artificial neural network. Journal of Hydrology 216(1-2): 32-55.
    • (1999) Journal of Hydrology , vol.216 , Issue.1-2 , pp. 32-55
    • Sajikumar, N.1    Thandaveswara, B.S.2
  • 28
    • 0342506462 scopus 로고    scopus 로고
    • Application of neural network technique to rainfall-runoff modeling
    • Shamseldin AY. 1997. Application of neural network technique to rainfall-runoff modeling. Journal of Hydrology 199: 272-294.
    • (1997) Journal of Hydrology , vol.199 , pp. 272-294
    • Shamseldin, A.Y.1
  • 31
    • 0037197571 scopus 로고    scopus 로고
    • A data-driven algorithm for constructing artificial neural network rainfall-runoff models
    • Sudheer KP, Gosain AK, Ramasastri KS. 2002. A data-driven algorithm for constructing artificial neural network rainfall-runoff models. Hydrological Processes 16: 1325-1330.
    • (2002) Hydrological Processes , vol.16 , pp. 1325-1330
    • Sudheer, K.P.1    Gosain, A.K.2    Ramasastri, K.S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.