Discussion of “Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall” by M. R. Mustafa, R. B. Rezaur, S. Saiedi, H. Rahardjo, and M. H. Isa
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VIEW THE ORIGINAL ARTICLEPublication: Journal of Hydrologic Engineering
Volume 19, Issue 6
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References
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Deka, P., and Chandramouli, V. (2003). “A fuzzy neural network model for deriving the river stage-discharge relationship.” Hydrol. Sci. J., 48(2), 197–209.
Maier, H. R., and Dandy, G. C. (2000). “Neural networks for the prediction and forecasting of water resources variables: A review of modeling issues and applications.” Environ. Model. Software, 15(1), 101–124.
Nourani, V., Komasi, M., and Mano, A. (2009). “A multivariate ANN–wavelet approach for rainfall–runoff modeling.” Water Resour. Manage., 23(14), 2877–2894.
Sudheer, K. P., Gosain, A. K., Rangan, D. M., and Saheb, S. M. (2002). “Modelling evaporation using an artificial neural network algorithm.” Hydrol. Processes, 16(16), 3189–3202.
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Journal of Hydrologic Engineering
Volume 19 • Issue 6 • June 2014
Pages: 1271
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Apr 8, 2013
Accepted: May 8, 2013
Published online: May 15, 2014
Published in print: Jun 1, 2014
Discussion open until: Oct 15, 2014
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Professor, Civil Engineering Dept., Canik Basari Univ., Samsun 55080, Turkey. E-mail: [email protected]
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