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基于神经网络模型的绿色金融评估。

Green Finance Evaluation Based on Neural Network Model.

机构信息

School of Economics and Management, Huzhou College, Huzhou, Zhejiang 313000, China.

出版信息

Comput Intell Neurosci. 2022 Aug 17;2022:4803072. doi: 10.1155/2022/4803072. eCollection 2022.

Abstract

The weights of green finance indicators are established in accordance with the AHP in order to suggest an evaluation system that is more thorough and reasonable and to construct an evaluation index system. The findings indicate that the growth of urban green finance is more closely correlated with the development of environmental protection businesses, capital allocation efficiency, and governmental and social capital support. Regulation of consumption also has a significant impact. In order to encourage the growth of urban green finance, this paper analyzes the scoring outcomes and changes for each city and offers solutions and recommendations.

摘要

根据层次分析法(AHP)确定绿色金融指标权重,提出更全面、合理的评价体系,构建评价指标体系。研究结果表明,城市绿色金融的增长与环保产业发展、资本配置效率、政府和社会资本支持的关系更为密切,消费监管也具有显著影响。为了促进城市绿色金融的发展,本文对各城市的得分结果和变化进行分析,并提出解决方案和建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58f3/9402347/03513599c52d/CIN2022-4803072.001.jpg

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