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Volumn 340, Issue 1-2, 2007, Pages 1-11

A simple neural network model for the determination of aquifer parameters

Author keywords

Artificial neural network; Back propagation; Confined aquifer parameters; Levenberg Marquardt (LM) training algorithm; Principal component analysis

Indexed keywords

ALGORITHMS; BACKPROPAGATION; NEURAL NETWORKS; PARAMETER ESTIMATION; PATTERN MATCHING; PRINCIPAL COMPONENT ANALYSIS;

EID: 34249898039     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2007.03.017     Document Type: Article
Times cited : (104)

References (39)
  • 1
    • 0026836829 scopus 로고
    • A neural-network approach to the determination of aquifer parameters
    • Aziz A.R.A., and Wong K.V. A neural-network approach to the determination of aquifer parameters. Ground Water 30 2 (1992) 164-166
    • (1992) Ground Water , vol.30 , Issue.2 , pp. 164-166
    • Aziz, A.R.A.1    Wong, K.V.2
  • 2
    • 0037199710 scopus 로고    scopus 로고
    • Aquifer parameters determination for large diameter wells using neural network approach
    • Balkhair K.S. Aquifer parameters determination for large diameter wells using neural network approach. Journal of Hydrology 265 1-4 (2002) 118-128
    • (2002) Journal of Hydrology , vol.265 , Issue.1-4 , pp. 118-128
    • Balkhair, K.S.1
  • 3
    • 0029849763 scopus 로고    scopus 로고
    • Variation in discharge dissolved organic carbon and nitrogen export form terrestrial basins with changes in climate: a neural network approach
    • Clair T.A., and Ehrman J.M. Variation in discharge dissolved organic carbon and nitrogen export form terrestrial basins with changes in climate: a neural network approach. Limnology Oceanography 41 (1996) 921-927
    • (1996) Limnology Oceanography , vol.41 , pp. 921-927
    • Clair, T.A.1    Ehrman, J.M.2
  • 4
    • 0034993945 scopus 로고    scopus 로고
    • Artificial neural network modeling of water table depth fluctuations
    • Coulibaly P., Anctil F., Aravena R., and Bobee B. Artificial neural network modeling of water table depth fluctuations. Water Resources Research 37 4 (2001) 885-896
    • (2001) Water Resources Research , vol.37 , Issue.4 , pp. 885-896
    • Coulibaly, P.1    Anctil, F.2    Aravena, R.3    Bobee, B.4
  • 5
    • 20344369583 scopus 로고    scopus 로고
    • Groundwater level forecasting using artificial neural networks
    • Daliakopoulos I.N., Coulibaly P., and Tsanis I.K. Groundwater level forecasting using artificial neural networks. Journal of Hydrology 309 1-4 (2005) 229-240
    • (2005) Journal of Hydrology , vol.309 , Issue.1-4 , pp. 229-240
    • Daliakopoulos, I.N.1    Coulibaly, P.2    Tsanis, I.K.3
  • 9
    • 31044452344 scopus 로고    scopus 로고
    • Using neural networks for parameter estimation in ground water
    • Garcia L.A., and Shigidi A. Using neural networks for parameter estimation in ground water. Journal of Hydrology 318 1-4 (2006) 215-231
    • (2006) Journal of Hydrology , vol.318 , Issue.1-4 , pp. 215-231
    • Garcia, L.A.1    Shigidi, A.2
  • 10
    • 0033627322 scopus 로고    scopus 로고
    • The application of artificial neural networks for the prediction of water quality of polluted aquifer
    • Gumrah F., Oz B., Guler B., and Evin S. The application of artificial neural networks for the prediction of water quality of polluted aquifer. Water Air and Soil Pollution 119 1-4 (2000) 275-294
    • (2000) Water Air and Soil Pollution , vol.119 , Issue.1-4 , pp. 275-294
    • Gumrah, F.1    Oz, B.2    Guler, B.3    Evin, S.4
  • 13
    • 0029413797 scopus 로고
    • Artificial neural network modeling of the rainfall-runoff process
    • Hsu K.L., Gupta H.V., and 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.L.1    Gupta, H.V.2    Sorooshian, S.3
  • 17
    • 19744366167 scopus 로고    scopus 로고
    • On the use of neural networks to evaluate groundwater levels in fractured media
    • Lallahem S., Mania J., Hani A., and Najjar Y. On the use of neural networks to evaluate groundwater levels in fractured media. Journal of Hydrology 307 1-4 (2005) 92-111
    • (2005) Journal of Hydrology , vol.307 , Issue.1-4 , pp. 92-111
    • Lallahem, S.1    Mania, J.2    Hani, A.3    Najjar, Y.4
  • 18
    • 1842433866 scopus 로고    scopus 로고
    • A spatial interpolation method based on radial basis function networks incorporating a semivariogram model
    • Lin G.F., and Chen L.H. A spatial interpolation method based on radial basis function networks incorporating a semivariogram model. Journal of Hydrology 288 3-4 (2004) 288-298
    • (2004) Journal of Hydrology , vol.288 , Issue.3-4 , pp. 288-298
    • Lin, G.F.1    Chen, L.H.2
  • 19
    • 1642387025 scopus 로고    scopus 로고
    • A non-linear rainfall-runoff model using radial basis function network
    • Lin G.F., and Chen L.H. A non-linear rainfall-runoff model using radial basis function network. Journal of Hydrology 289 1-4 (2004) 1-8
    • (2004) Journal of Hydrology , vol.289 , Issue.1-4 , pp. 1-8
    • Lin, G.F.1    Chen, L.H.2
  • 20
    • 28744432693 scopus 로고    scopus 로고
    • An improved neural network approach to the determination of aquifer parameters
    • Lin G.F., and Chen G.R. An improved neural network approach to the determination of aquifer parameters. Journal of Hydrology 316 1-4 (2006) 281-289
    • (2006) Journal of Hydrology , vol.316 , Issue.1-4 , pp. 281-289
    • Lin, G.F.1    Chen, G.R.2
  • 21
    • 0029663621 scopus 로고    scopus 로고
    • The use of artificial neural networks for the prediction of water quality parameters
    • Maier H.R., and Dandy G.C. The use of artificial neural networks for the prediction of water quality parameters. Water Resources Research 32 4 (1996) 1013-1022
    • (1996) Water Resources Research , vol.32 , Issue.4 , pp. 1013-1022
    • Maier, H.R.1    Dandy, G.C.2
  • 22
    • 0032855262 scopus 로고    scopus 로고
    • Empirical comparison of various methods for training feed-forward neural networks for salinity forecasting
    • Maier H.R., and Dandy G.C. Empirical comparison of various methods for training feed-forward neural networks for salinity forecasting. Water Resources Research 32 8 (1999) 2591-2596
    • (1999) Water Resources Research , vol.32 , Issue.8 , pp. 2591-2596
    • Maier, H.R.1    Dandy, G.C.2
  • 23
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for the prediction and forecasting of water resources variables: a review of modeling issues and applications
    • Maier H.R., and Dandy G.C. Neural networks for the prediction and forecasting of water resources variables: a review of modeling issues and applications. Environmental Modelling and Software 15 (2000) 101-124
    • (2000) Environmental Modelling and Software , vol.15 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 24
    • 34249898503 scopus 로고    scopus 로고
    • MATLAB, Release 14, 2004, by the Math Works, Inc.
  • 25
    • 51249194645 scopus 로고
    • A logical calculus of the ideas immanent in nervous activity
    • McCulloch W., and Pitts W. A logical calculus of the ideas immanent in nervous activity. The Bulletin of Mathematical Biophysics 5 (1943) 113-115
    • (1943) The Bulletin of Mathematical Biophysics , vol.5 , pp. 113-115
    • McCulloch, W.1    Pitts, W.2
  • 26
    • 0027089138 scopus 로고
    • Examining large databases: a chemometric approach using Principal Component Analysis
    • Meglen R.R. Examining large databases: a chemometric approach using Principal Component Analysis. Mar. Chem. 39 (1992) 17-237
    • (1992) Mar. Chem. , vol.39 , pp. 17-237
    • Meglen, R.R.1
  • 27
    • 0012733832 scopus 로고    scopus 로고
    • Stream hydrological and ecological responses to climate change assessed with an artificial neural network
    • Poff N.L., Tokar S., and Johnson P. Stream hydrological and ecological responses to climate change assessed with an artificial neural network. Limnology Oceanography 41 (1996) 857-863
    • (1996) Limnology Oceanography , vol.41 , pp. 857-863
    • Poff, N.L.1    Tokar, S.2    Johnson, P.3
  • 28
    • 0028193610 scopus 로고
    • Characterization of aquifer properties using artificial neural network: neural kriging
    • Rizzo D.M., and Dougherty D.E. Characterization of aquifer properties using artificial neural network: neural kriging. Water Resources Research 30 2 (1994) 483-497
    • (1994) Water Resources Research , vol.30 , Issue.2 , pp. 483-497
    • Rizzo, D.M.1    Dougherty, D.E.2
  • 29
    • 0028174533 scopus 로고
    • Optimization of groundwater remediation using artificial neural network with parallel solute transport modeling
    • Rogers L.L., and Dowla F.U. Optimization of groundwater remediation using artificial neural network with parallel solute transport modeling. Water Resources Research 30 2 (1994) 457-481
    • (1994) Water Resources Research , vol.30 , Issue.2 , pp. 457-481
    • Rogers, L.L.1    Dowla, F.U.2
  • 30
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • Rumelhart D.E., and David E. (Eds), MIT Press, Cambridge, MA
    • Rumelhart D.E., Hinton G.R., and Williams R.J. Learning internal representations by error propagation. In: Rumelhart D.E., and David E. (Eds). Parallel Distributed Processing (1986), MIT Press, Cambridge, MA 318-362
    • (1986) Parallel Distributed Processing , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.R.2    Williams, R.J.3
  • 31
    • 0342506462 scopus 로고    scopus 로고
    • Application of a neural network technique to rainfall-runoff modeling
    • Shamseldin A.Y. Application of a neural network technique to rainfall-runoff modeling. Journal of Hydrology, Amsterdam 199 (1997) 272-294
    • (1997) Journal of Hydrology, Amsterdam , vol.199 , pp. 272-294
    • Shamseldin, A.Y.1
  • 32
    • 84981756619 scopus 로고
    • The relationship between the lowering of the piezometric surface and the rate and duration of discharge of a well using ground-water storage
    • Theis C.V. The relationship between the lowering of the piezometric surface and the rate and duration of discharge of a well using ground-water storage. Transactions American Geophysical Union 16 (1935) 519-524
    • (1935) Transactions American Geophysical Union , vol.16 , pp. 519-524
    • Theis, C.V.1
  • 34
    • 0034694775 scopus 로고    scopus 로고
    • Comparison of short-term rainfall prediction models for real-time flood forecasting
    • Toth E., Brath A., and Montanari A. Comparison of short-term rainfall prediction models for real-time flood forecasting. Journal of Hydrology 239 (2000) 132-147
    • (2000) Journal of Hydrology , vol.239 , pp. 132-147
    • Toth, E.1    Brath, A.2    Montanari, A.3
  • 36
    • 34249873661 scopus 로고    scopus 로고
    • Wit, K.E., 1963. The hydraulic characteristics of the Oude Korendijk podler, calculated from pumping test data and laboratory measurements of core samples (in Dutch). Inst. Land and Water Manag. Res., Wageningen, Report No. 190, 24 pp.
  • 38
    • 0346509535 scopus 로고    scopus 로고
    • Approaching the inverse problem of parameter estimation in groundwater models by means of artificial neural networks
    • Zio E. Approaching the inverse problem of parameter estimation in groundwater models by means of artificial neural networks. Progress in Nuclear Energy 31 3 (1997) 303-315
    • (1997) Progress in Nuclear Energy , vol.31 , Issue.3 , pp. 303-315
    • Zio, E.1
  • 39
    • 0028668180 scopus 로고
    • Principal component analysis in the evaluation of environmental data
    • Zitko V. Principal component analysis in the evaluation of environmental data. Mar. Pollut. Bull. 23 4 (1994) 718-722
    • (1994) Mar. Pollut. Bull. , vol.23 , Issue.4 , pp. 718-722
    • Zitko, V.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.