An Empirical Study on Low Carbon Development Model of China's Energy Economy Based on Neural Networks

Kangli Xiang, Xianan Huang, Li Zhang
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Abstract

This paper on the low-carbon development model at home and abroad is introduced, on the basis of further defined related concepts of low carbon development, and then on the basis of familiar with the related concepts, introduces the related carbon decomposition model, then the particle swarm optimization (pso) algorithm and BP neural network for the corresponding introduction, on the basis of related theory, multi-dimensional decomposition model of carbon productivity in our empirical study, analysis and comparison in compared with the base in different industries in various provinces the contribution values of different influence factors on the carbon productivity in our country.
基于神经网络的中国能源经济低碳发展模型实证研究
本文在对国内外低碳发展模式进行介绍的基础上,进一步界定了低碳发展的相关概念,然后在熟悉相关概念的基础上,介绍了相关的碳分解模型,然后对粒子群优化(pso)算法和BP神经网络进行了相应的介绍,在相关理论的基础上,对碳生产率的多维分解模型进行了实证研究。分析比较了不同省份不同行业不同影响因素对我国碳生产率的贡献值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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