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基于 BP 神经网络的水库移民可持续发展评价

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

机构信息

National Research Center for Resettlement (NRCR), Hohai University, 1 Xikang Road, Nanjing 210098, China.

School of Public Administration, Hohai University, 1 Xikang Road, Nanjing 210098, China.

出版信息

Int J Environ Res Public Health. 2018 Jan 18;15(1):146. doi: 10.3390/ijerph15010146.

Abstract

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.

摘要

移民安置不仅会影响移民的生产活动和生活,还会直接或间接地影响电站的正常运行、移民的可持续发展以及区域社会稳定。因此,必须建立一个符合中国国情的科学水库移民可持续发展评价指标体系,不仅要促进水库移民研究,还要改进移民实践。本文以乌江梯级水电站移民安置为例,建立了基于反向传播(BP)神经网络的移民可持续发展评价指标体系,该体系可在中国采用。评估结果表明,乌江梯级水电站的移民安置是可持续的,这一评估支持了国家政策法规不断完善和移民安置不断改善的结论。研究结果为发展中国家的水电水库移民安置提供了参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f35c/5800245/8c48a7580f96/ijerph-15-00146-g001.jpg

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