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• W3015171039 startingPage "63134" @default.
• W3015171039 abstract "Given that there has been ecological degradation for a long time in Shanxi Province, China. This research addresses this situation by analyzing the energy structure and environmental risk in the past and in the future. Consequently, this study uses two indicator systems, ecosystem interaction system and environmental risk representation, to illustrate the environmental risk in an energy intensive region of China. And we build a BP-SVM model applying a back-propagation (BP) neural network and support vector machine (SVM) arithmetic to predict the future ecology-economy-society system interactions in Shanxi Province. At last, we classify the risk rank by using environmental risk representation indicators. The main conclusions from this research are as follows: Firstly, two indicator systems have advantages in describing the ecological-economy-society interaction especially the human society's impact on the ecosystem over a single indicator system. Secondly, by the BP-SVM model, there is a relatively high ecological risk rank in next few years in Shanxi Province, although it fluctuates occasionally. Finally, this study not only offers recommendations for the government to develop policies to transform from a coal-energy based system to a clean, safe, and efficient modern energy system, but also points out the implications for government administrations in energy intensive areas of developing countries to guide the economic transformation." @default.
• W3015171039 created "2020-04-10" @default.
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• W3015171039 date "2020-01-01" @default.
• W3015171039 modified "2023-10-16" @default.
• W3015171039 title "Environmental Risk and Policy Choices in an Energy Intensive Region of China—An Empirical Study in Shanxi Province" @default.
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• W3015171039 doi "https://doi.org/10.1109/access.2020.2984013" @default.
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