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Open AccessArticle

The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network

by Li Huang 1,2, Jian Huang 1,3 and Wei Wang 4,*
1
National Research Center for Resettlement (NRCR), Hohai University, 1 Xikang Road, Nanjing 210098, China
2
School of Public Administration, Hohai University, 1 Xikang Road, Nanjing 210098, China
3
Business School, Hohai University, 1 Xikang Road, Nanjing 210098, China
4
College of Harbor, Coastal and Offshore Engineering, Hohai University, 1 Xikang Road, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(1), 146; https://doi.org/10.3390/ijerph15010146
Received: 11 November 2017 / Revised: 2 January 2018 / Accepted: 16 January 2018 / Published: 18 January 2018
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
Resettlement affects not only the resettlers’ production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir resettlement must be established that fits Chinese national conditions and not only promotes reservoir resettlement research but also improves resettlement practice. This essay builds an evaluation index system for resettlers’ sustainable development based on a back-propagation (BP) neural network, which can be adopted in China, taking the resettlement necessitated by step hydropower stations along the Wujiang River cascade as an example. The assessment results show that the resettlement caused by step power stations along the Wujiang River is sustainable, and this evaluation supports the conclusion that national policies and regulations, which are undergoing constant improvement, and resettlement has increasingly improved. The results provide a reference for hydropower reservoir resettlement in developing countries. View Full-Text
Keywords: sustainable development assessment; reservoir resettlement; BP neural network sustainable development assessment; reservoir resettlement; BP neural network
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MDPI and ACS Style

Huang, L.; Huang, J.; Wang, W. The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network. Int. J. Environ. Res. Public Health 2018, 15, 146.

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