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

机译:基于神经网络的中国能源经济低碳发展模式的实证研究

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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.
机译:本文介绍了国内外低碳开发模式,在进一步定义的低碳发展概念的基础上介绍,然后在熟悉相关概念的基础上,介绍相关的碳分解模型,然后 粒子群优化(PSO)算法和BP神经网络相应介绍,基于相关理论的基础,在我们的实证研究,分析和比较中的多维分解模型与各省不同行业的基础相比 不同影响因素对我国碳生产率的贡献价值。

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