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Volumn 318, Issue 1-4, 2006, Pages 232-249

Integration of artificial neural networks with conceptual models in rainfall-runoff modeling

Author keywords

Artificial neural networks; Conceptual model; Lumped model; Performance measures; Rainfall runoff modeling; Semi distributed model

Indexed keywords

CATCHMENTS; MAPPING; NEURAL NETWORKS;

EID: 31044455061     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2005.06.017     Document Type: Article
Times cited : (113)

References (36)
  • 1
    • 0034174396 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology. I: Preliminary concepts
    • ASCE Task Committee on application of Artificial Neural Networks in Hydrology
    • ASCE Task Committee on application of Artificial Neural Networks in Hydrology Artificial neural networks in hydrology. I: preliminary concepts J. Hydr. Eng. 5 2 2000 124 137
    • (2000) J. Hydr. Eng. , vol.5 , Issue.2 , pp. 124-137
  • 2
    • 0034174280 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology. II: Hydrologic applications
    • ASCE Committee on application of Artificial Neural Networks in Hydrology
    • ASCE Committee on application of Artificial Neural Networks in Hydrology Artificial neural networks in hydrology. II: hydrologic applications J. Hydrologic Engrg. 5 2 2000 115 123
    • (2000) J. Hydrologic Engrg. , vol.5 , Issue.2 , pp. 115-123
  • 4
    • 0036499322 scopus 로고    scopus 로고
    • Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural networks
    • A.J. Cannon, and P.H. Whitfield Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural networks J. Hydrol. 259 2002 136 151
    • (2002) J. Hydrol. , vol.259 , pp. 136-151
    • Cannon, A.J.1    Whitfield, P.H.2
  • 5
    • 31044447021 scopus 로고    scopus 로고
    • M.Sc thesis, Department of Engineering Hydrology, National University of Ireland, Galway, Republic of Ireland.
    • Chen J.Y., 1998. Application of GIS in Conceptual Rainfall-Runoff Modeling. M.Sc thesis, Department of Engineering Hydrology, National University of Ireland, Galway, Republic of Ireland.
    • (1998) Application of GIS in Conceptual Rainfall-Runoff Modeling
    • Chen, J.Y.1
  • 7
    • 0032005702 scopus 로고    scopus 로고
    • An artificial neural network approach to rainfall-runoff modeling
    • C.W. Dawson, and R. Wilby An artificial neural network approach to rainfall-runoff modeling Hydr. Sci. 43 1 1998 47 66
    • (1998) Hydr. Sci. , vol.43 , Issue.1 , pp. 47-66
    • Dawson, C.W.1    Wilby, R.2
  • 9
    • 0024866495 scopus 로고
    • On the approximate realization of continuous mappings by neural networks
    • K. Funahashi On the approximate realization of continuous mappings by neural networks Neural Networks 2 1989 183 192
    • (1989) Neural Networks , vol.2 , pp. 183-192
    • Funahashi, K.1
  • 10
    • 0034702917 scopus 로고    scopus 로고
    • Runoff analysis in humid forest catchment with artificial neural network
    • M.R. Gautam, K. Watanabe, and H. Saegusa Runoff analysis in humid forest catchment with artificial neural network J. Hydrol. 235 2000 117 136
    • (2000) J. Hydrol. , vol.235 , pp. 117-136
    • Gautam, M.R.1    Watanabe, K.2    Saegusa, H.3
  • 11
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • K. Hornik, M. Stinchcombe, and H. White Multilayer feedforward networks are universal approximators Neural Networks 2 5 1989 359 366
    • (1989) Neural Networks , vol.2 , Issue.5 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 12
    • 0029413797 scopus 로고
    • Artificial neural network modeling of the rainfall-runoff process
    • Hsu, Kuo-lin, H.V. Gupta, and S. Sorooshian Artificial neural network modeling of the rainfall-runoff process Water Resour. Res. 31 10 1995 2517 2530
    • (1995) Water Resour. Res. , vol.31 , Issue.10 , pp. 2517-2530
    • Hsu1    Kuo-Lin2    Gupta, H.V.3    Sorooshian, S.4
  • 13
    • 0019228050 scopus 로고
    • Adaptive filtering through detection of isolated transient errors in rainfall-runoff models
    • P.K. Kitanidis, and R.L. Bras Adaptive filtering through detection of isolated transient errors in rainfall-runoff models Water Resour. Res. 16 4 1980 740 748
    • (1980) Water Resour. Res. , vol.16 , Issue.4 , pp. 740-748
    • Kitanidis, P.K.1    Bras, R.L.2
  • 14
    • 0019228050 scopus 로고
    • Real-time forecasting with a conceptual hydrological model
    • P.K. Kitanidis, and R.L. Bras Real-time forecasting with a conceptual hydrological model Water Resour. Res. 16 4 1980 740 748
    • (1980) Water Resour. Res. , vol.16 , Issue.4 , pp. 740-748
    • Kitanidis, P.K.1    Bras, R.L.2
  • 15
    • 0037142398 scopus 로고    scopus 로고
    • Hybrid neural network modeling of a full-scale industrial wastewater treatment process
    • D.S. Lee, C.O. Jeon, J.M. Park, and K.S. Chang Hybrid neural network modeling of a full-scale industrial wastewater treatment process Biotechnol. Bioeng. 78 6 2002 670 682
    • (2002) Biotechnol. Bioeng. , vol.78 , Issue.6 , pp. 670-682
    • Lee, D.S.1    Jeon, C.O.2    Park, J.M.3    Chang, K.S.4
  • 16
    • 0014776873 scopus 로고
    • River flow forecasting through conceptual models, part 1. a discussion of principles
    • J.E. Nash, and J.V. Sutcliffe River flow forecasting through conceptual models, part 1. A discussion of principles J. Hydrol. 10 1970 282 290
    • (1970) J. Hydrol. , vol.10 , pp. 282-290
    • Nash, J.E.1    Sutcliffe, J.V.2
  • 17
    • 0001535952 scopus 로고
    • River flow forecasting through conceptual models. Part 2. the Brosna catchment at Ferbane
    • P.E. O'Connell, J.E. Nash, and J.P. Farrell River flow forecasting through conceptual models. Part 2. The Brosna catchment at Ferbane J. Hydrol. 10 1970 317 329
    • (1970) J. Hydrol. , vol.10 , pp. 317-329
    • O'Connell, P.E.1    Nash, J.E.2    Farrell, J.P.3
  • 18
    • 31044446407 scopus 로고    scopus 로고
    • Unpublished Lecture Notes. Department of Engineering Hydrology, National University of Ireland, Galway.
    • O'Connor, K.M., 1997. Applied hydrology I-deterministic. Unpublished Lecture Notes. Department of Engineering Hydrology, National University of Ireland, Galway.
    • (1997) Applied Hydrology I-deterministic
    • O'Connor, K.M.1
  • 19
    • 0001723141 scopus 로고
    • An automatic method for finding the greatest or least value of a function
    • H.H. Rosenbrock An automatic method for finding the greatest or least value of a function Comput. J. 3 1960 175 184
    • (1960) Comput. J. , vol.3 , pp. 175-184
    • Rosenbrock, H.H.1
  • 20
    • 0033535432 scopus 로고    scopus 로고
    • A non-linear rainfall-runoff model using an artificial neural network
    • N. Sajikumar, and B.S. Thandaveswara A non-linear rainfall-runoff model using an artificial neural network J. Hydrol. 216 1999 32 55
    • (1999) J. Hydrol. , vol.216 , pp. 32-55
    • Sajikumar, N.1    Thandaveswara, B.S.2
  • 21
    • 0034739743 scopus 로고    scopus 로고
    • Application of a geographic information system for conceptual rainfall-runoff modeling
    • A.H. Schumann, R. Funke, and G.A. Schultz Application of a geographic information system for conceptual rainfall-runoff modeling J. Hydrol. 240 2000 45 61
    • (2000) J. Hydrol. , vol.240 , pp. 45-61
    • Schumann, A.H.1    Funke, R.2    Schultz, G.A.3
  • 22
    • 0342506462 scopus 로고    scopus 로고
    • Application of a neural network technique to rainfall-runoff modeling
    • A.Y. Shamseldin Application of a neural network technique to rainfall-runoff modeling J. Hydrol. 199 1997 272 294
    • (1997) J. Hydrol. , vol.199 , pp. 272-294
    • Shamseldin, A.Y.1
  • 23
    • 31044440186 scopus 로고
    • Neural-network models of rainfall-runoff process
    • J. Smith, and R.B. Eli Neural-network models of rainfall-runoff process J. Water Resour. Plng. Mgmt., ASCE 4 3 1995 232 239
    • (1995) J. Water Resour. Plng. Mgmt., ASCE , vol.4 , Issue.3 , pp. 232-239
    • Smith, J.1    Eli, R.B.2
  • 24
    • 84946640734 scopus 로고
    • Sequential application of simplex design in optimisation and evolutionary design
    • W. Spendy, G.R. Hext, and F.R. Himsworth Sequential application of simplex design in optimisation and evolutionary design Technometrics 4 1962 441 461
    • (1962) Technometrics , vol.4 , pp. 441-461
    • Spendy, W.1    Hext, G.R.2    Himsworth, F.R.3
  • 25
    • 0008275576 scopus 로고
    • On the analysis of runoff structure about several Japanese rivers
    • M. Sugawara On the analysis of runoff structure about several Japanese rivers Jap. J. Geophys. 2 4 1961 1 76
    • (1961) Jap. J. Geophys. , vol.2 , Issue.4 , pp. 1-76
    • Sugawara, M.1
  • 27
    • 0030274099 scopus 로고    scopus 로고
    • Application of an empirical infiltration quation in the SMAR conceptual model
    • B.Q. Tan, and K.M. O'Connor Application of an empirical infiltration quation in the SMAR conceptual model J. Hydrol. 185 1996 275 295
    • (1996) J. Hydrol. , vol.185 , pp. 275-295
    • Tan, B.Q.1    O'Connor, K.M.2
  • 28
    • 0033167344 scopus 로고    scopus 로고
    • Rainfall-runoff modeling using artificial neural network
    • A.S. Tokar, and P.A. Johnson Rainfall-runoff modeling using artificial neural network J. Hydr. Eng., ASCE 4 3 1999 232 239
    • (1999) J. Hydr. Eng., ASCE , vol.4 , Issue.3 , pp. 232-239
    • Tokar, A.S.1    Johnson, P.A.2
  • 29
    • 0034174397 scopus 로고    scopus 로고
    • Precipitation-runoff modeling using artificial neural networks and concettual models
    • A.S. Tokar, and M. Markus Precipitation-runoff modeling using artificial neural networks and concettual models J. Hydr. Eng., ASCE 5 2 2000 156 161
    • (2000) J. Hydr. Eng., ASCE , vol.5 , Issue.2 , pp. 156-161
    • Tokar, A.S.1    Markus, M.2
  • 30
    • 0343052706 scopus 로고    scopus 로고
    • An efficient model development strategy for bioprocesses based on neural networks in macroscopic balance
    • H.J.L. Van Can, H.A.B. te Braake, C. Hellinga, K.C.A.M Luyben, and J.J. Heijnen An efficient model development strategy for bioprocesses based on neural networks in macroscopic balance Biotechnol. Bioeng. 54 1997 549 566
    • (1997) Biotechnol. Bioeng. , vol.54 , pp. 549-566
    • Van Can, H.J.L.1    Te Braake, H.A.B.2    Hellinga, C.3    Luyben, A.M.4    Heijnen, J.J.5
  • 31
    • 0026266630 scopus 로고
    • The genetic algorithm and its application to calibrating conceptual rainfall-runoff models
    • Q.J. Wang The genetic algorithm and its application to calibrating conceptual rainfall-runoff models Water Resour. Res. 27 9 1991 2367 2471
    • (1991) Water Resour. Res. , vol.27 , Issue.9 , pp. 2367-2471
    • Wang, Q.J.1
  • 32
    • 0037466126 scopus 로고    scopus 로고
    • Geomorphology-based artifical neural networks (GANNs) for estimation of direct runoff over watersheds
    • B. Zhang, and R.S. Govindaraju Geomorphology-based artifical neural networks (GANNs) for estimation of direct runoff over watersheds J. Hydrol. 273 1-4 2003 18 34
    • (2003) J. Hydrol. , vol.273 , Issue.1-4 , pp. 18-34
    • Zhang, B.1    Govindaraju, R.S.2
  • 33
    • 0026895285 scopus 로고
    • The Xinanjiang model applied in China
    • R.J. Zhao The Xinanjiang model applied in China J. Hydrol. 135 1992 1992 371 381
    • (1992) J. Hydrol. , vol.135 , Issue.1992 , pp. 371-381
    • Zhao, R.J.1
  • 34
    • 0000626643 scopus 로고
    • The Xinanjiang model
    • V.P. Singh Water Resources Publications Littleton, CO
    • R.J. Zhao, and X.R. Liu The Xinanjiang model V.P. Singh Computer Models of Watershed Hydrology 1995 Water Resources Publications Littleton, CO
    • (1995) Computer Models of Watershed Hydrology
    • Zhao, R.J.1    Liu, X.R.2
  • 36
    • 0030973287 scopus 로고    scopus 로고
    • Modeling nutrient dynamics in sequencing batch reactor
    • H. Zhao, O.J. Hao, T.J. McAvoy, and C-H. Chang Modeling nutrient dynamics in sequencing batch reactor J. Environ. Eng. 123 1997 311 319
    • (1997) J. Environ. Eng. , vol.123 , pp. 311-319
    • Zhao, H.1    Hao, O.J.2    McAvoy, T.J.3    Chang, C.-H.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.