Discussions and Closures
Feb 16, 2018

Closure to “Improving Prediction of Dam Failure Peak Outflow Using Neuroevolution Combined with K-Means Clustering” by Amir Hossein Eghbali, Kourosh Behzadian, Farhad Hooshyaripor, Raziyeh Farmani, and Andrew P. Duncan

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Publication: Journal of Hydrologic Engineering
Volume 23, Issue 5

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References

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Hooshyaripor, F., Tahershamsi, A., and Golian, S. (2014). “Application of copula method and neural networks for predicting peak outflow from breached embankments.” J. Hydro-Environ. Res., 8(3), 292–303.
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Pierce, M. W., Thornton, C. I., and Abt, S. R. (2010). “Predicting peak outflow from breached embankment dams.” J. Hydrol. Eng., 338–349.
Thornton, C. I., Pierce, M. W., and Abt, S. R. (2011). “Enhanced predictions for peak outflow from breached embankment dams.” J. Hydrol. Eng., 81–88.
Wahl, T. L. (1998). “Prediction of embankment dam breach parameters—A literature review and needs assessment.”, U.S. Bureau of Reclamation, Denver.
Wahl, T. L. (2014). “Evaluation of erodibility-based embankment 144 dam breach equations.”, U.S. Dept. of the Interior, Denver.
Xu, Y., and Zhang, L. M. (2009). “Breaching parameters for earth and rockfill dams.” J. Geotech. Geoenviron. Eng., 1957–1970.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 23Issue 5May 2018

History

Received: Oct 2, 2017
Accepted: Nov 3, 2017
Published online: Feb 16, 2018
Published in print: May 1, 2018
Discussion open until: Jul 16, 2018

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Authors

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Farhad Hooshyaripor
Assistant Professor, Dept. of Civil Engineering, Science and Research Branch, Islamic Azad Univ., 14778-93855 Tehran, Iran.
Senior Lecturer, School of Computing and Engineering, Univ. of West London, London W5 5RF, U.K. (corresponding author). ORCID: https://orcid.org/0000-0002-1459-8408. E-mail: [email protected]

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