Loss prediction of mountain flood disaster in villages and towns based on rough set RBF neural network-Reference-Cited by-同舟云学术

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Loss prediction of mountain flood disaster in villages and towns based on rough set RBF neural network

Published:2021-03-29 Issue:4 Volume:34 Page:2513-2524
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Zhang Yu,Hao Yonghe

Funder

Characteristic Innovation Projects of Guangdong Province Education Program

Science and Technology Program of Guangdong Province

Science and Technology Special Fund Program of Guangdong Province

Rural Science and Technology Commissioner Program of Guangdong Province

Collaborative Innovation Center of Big Data Research and Application, JYU & GMIP

Research Achievement Award Cultivation Project, Jiaying University

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-021-05902-1.pdf

Reference25 articles.

1. Ying W, Xiao L, Xuesong Q et al (2016) Prediction-based survivable virtual network mapping against disaster failures. Networks 26(5):336–354

2. Sasaki D, Moriyama K, Ono Y (2018). Hidden common factors in disaster loss statistics: a case study analyzing the data of Nepal (special issue on the development of disaster statistics). J Disaster Res. 13(6): 1032–1038

3. Murray D, Joe C, Heather H (2016) Urban flood prediction and warning–challenges and solutions. Proc Water Environ Federation 2016(13):2237–2242

4. Li G (2019) An integrated model of rough set and radial basis function neural network for early warning of enterprise human resource crisis. Int J Fuzzy Syst 21(8):2462–2471

5. Jiang RC, Jiang XJ, Gu SX (2017) Current status and counter-measures for existing problems in mountain torrent disaster prevention and control in Yunnan Province. J Information Optimization Sci 38(7):1169–1179

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