Prediction of flooding in the downstream of the Three Gorges Reservoir based on a back propagation neural network optimized using the AdaBoost algorithm-Reference-Cited by-同舟云学术

Prediction of flooding in the downstream of the Three Gorges Reservoir based on a back propagation neural network optimized using the AdaBoost algorithm

Published:2021-03-01 Issue:2 Volume:107 Page:1559-1575
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Xiong Biao,Li Ruiping,Ren Dong,Liu Huigang,Xu Tao,Huang Yingping

Funder

the Natural Science Foundation for Innovation Group of Hubei Province, China

the National Key Research Program

Research Fund for Excellent Dissertation of China Three Gorges University

the Open Projects Fund of the Engineering Research Center of Hubei Agricultural Environment monitoring

Hubei Province Support Project of Introducing Foreign Talents and Intelligence

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology

Link

https://link.springer.com/content/pdf/10.1007/s11069-021-04646-4.pdf

Reference31 articles.

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3. Huang ML, Chou YC (2019) Combining a gravitational search algorithm, particle swarm optimization, and fuzzy rules to improve the classification performance of a feed-forward neural network. Comput Methods Programs Biomed 180:105016. https://doi.org/10.1016/j.cmpb.2019.105016

4. Huang L, Li X, Fang H, Yin D, Si Y, Wei J, Liu J, Hu X, Zhang L (2019) Balancing social, economic and ecological benefits of reservoir operation during the flood season: a case study of the Three Gorges Project, China. J Hydrol 572:422–434. https://doi.org/10.1016/j.jhydrol.2019.03.009

5. Jahangir MH, Mousavi Reineh SM, Abolghasemi M (2019) Spatial predication of flood zonation mapping in Kan River Basin, Iran, using artificial neural network algorithm. Weather Climate Extremes 25:100215. https://doi.org/10.1016/j.wace.2019.100215

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