The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network
AbstractResettlement 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
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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.
Huang L, Huang J, Wang W. The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network. International Journal of Environmental Research and Public Health. 2018; 15(1):146.Chicago/Turabian Style
Huang, Li; Huang, Jian; Wang, Wei. 2018. "The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network." Int. J. Environ. Res. Public Health 15, no. 1: 146.
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