Discussion of “Improved Particle Swarm Optimization–Based Artificial Neural Network for Rainfall-Runoff Modeling” by Mohsen Asadnia, Lloyd H. C. Chua, X. S. Qin, and Amin Talei
This article is a reply.
VIEW THE ORIGINAL ARTICLEPublication: Journal of Hydrologic Engineering
Volume 20, Issue 9
HE.1943-5584.0001201/asset/8a3e2a62-0079-4c23-ae8d-11366e5b470f/assets/(asce)he.1943-5584.0001201.fp.png)
Get full access to this article
View all available purchase options and get full access to this article.
References
Chau, K. W. (2006). “Particle swarm optimization training algorithm for ANNs in stage prediction of Shing Mun River.” J. Hydrol., 329(3–4), 363–367.
Chau, K. W. (2007). “A split-step particle swarm optimization algorithm in river stage forecasting.” J. Hydrol., 346(3–4), 131–135.
Cobaner, M., Seckin, G., and Kisi, O. (2008). “Initial assessment of bridge backwater using artificial neural network approach.” Can. J. Civ. Eng., 35(5), 500–510.
Coulibaly, P., Anctil, F., and Bobée, B. (1998). “Real time neural network based forecasting system for hydropower reservoirs.” Proc., First Int. Conf. on New Information Technologies for Decision Making in Civil Engineering, E. T. Miresco, ed., 1001–1011.
Hornik, K., Stinchcombe, M., and White, H. (1989). “Multilayer feed-forward networks are universal approximators.” Neural Netw., 2(5), 359–366.
Kisi, O. (2004). “Multi-layer perceptions with Levenberg–Marquardt training algorithm for suspended sediment concentration prediction and estimation.” Hydrol. Sci. J., 49(6), 1025–1040.
Kisi, O. (2007). “Streamflow forecasting using different artificial neural network algorithms.” J. Hydrol. Eng., 532–539.
Kisi, O. (2011). “Wavelet regression model as an alternative to neural networks for river stage forecasting.” Water Resour. Manage., 25(2), 579–600.
Sudheer, K. P., Gosain, A. K., Rangan, D. M., and Saheb, S. M. (2002). “Modelling evaporation using an artificial neural network algorithm.” Hydrol. Process., 16(16), 3189–3202.
Zhang, G., Patuwo, B. E., and Hu, M. Y. (1998). “Forecasting with artificial neural networks: The state of the art.” Int. J. Forecasting, 14(1), 35–62.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 20 • Issue 9 • September 2015
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Aug 26, 2014
Accepted: Sep 11, 2014
Published online: Feb 25, 2015
Discussion open until: Jul 25, 2015
Published in print: Sep 1, 2015
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.