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Identify and Assess Hydropower Project’s Multidimensional Social Impacts with Rough Set and Projection Pursuit Model

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  • Hui An
  • Wenjing Yang
  • Jin Huang
  • Ai Huang
  • Zhongchi Wan
  • Min An

Abstract

To realize the coordinated and sustainable development of hydropower projects and regional society, comprehensively evaluating hydropower projects’ influence is critical. Usually, hydropower project development has an impact on environmental geology and social and regional cultural development. Based on comprehensive consideration of complicated geological conditions, fragile ecological environment, resettlement of reservoir area, and other factors of future hydropower development in each country, we have constructed a comprehensive evaluation index system of hydropower projects, including 4 first-level indicators of social economy, environment, safety, and fairness, which contain 26 second-level indicators. To solve the problem that existing models cannot evaluate dynamic nonlinear optimization, a projection pursuit model is constructed by using rough set reduction theory to simplify the index. Then, an accelerated genetic algorithm based on real number coding is used to solve the model and empirical study is carried out with the Y hydropower station as a sample. The evaluation results show that the evaluation index system and assessment model constructed in our paper effectively reduce the subjectivity of index weight. Applying our model to the social impact assessment (SIA) of related international hydropower projects can not only comprehensively analyze the social impact of hydropower projects but also identify important social influencing factors and effectively analyze the social impact level of each dimension. Furthermore, SIA assessment can be conducive to project decision-making, avoiding social risks and social stability.

Suggested Citation

  • Hui An & Wenjing Yang & Jin Huang & Ai Huang & Zhongchi Wan & Min An, 2020. "Identify and Assess Hydropower Project’s Multidimensional Social Impacts with Rough Set and Projection Pursuit Model," Complexity, Hindawi, vol. 2020, pages 1-16, November.
  • Handle: RePEc:hin:complx:9394639
    DOI: 10.1155/2020/9394639
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    Cited by:

    1. Wei Pei & Lei Hao & Qiang Fu & Yongtai Ren & Tianxiao Li, 2023. "Study on Agricultural Drought Risk Assessment Based on Information Entropy and a Cluster Projection Pursuit Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 619-638, January.

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