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基于TOPSIS熵权的SARIMA模型对新能源汽车的生态研究
Research on the Ecological Impact of New Energy Vehicles Using the SARIMA Model Based on TOPSIS Entropy Weight

DOI: 10.12677/ORF.2024.141057, PP. 607-618

Keywords: 新能源汽车,TOPSIS熵权法,聚类,SARIMA,生态环境
New Energy Vehicles
, TOPSIS Method with Entropy Weighting, Clustering, SARIMA, Ecological Environment

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Abstract:

自2011年起,新能源汽车在政府的支持和鼓励下快速发展,已呈现出从政策驱动转向市场拉动的新发展阶段,而新能源汽车的发展对生态环境的影响也不容小觑。本文对我国各个省份新能源汽车的发展水平进行聚类划分,从中选择具有代表性的广州省,建立SO2,NOx,工业烟(粉)尘作为新能源汽车影响生态环境的指标,利用基于TOPSIS的熵权法对2007年到2021年时间序列的生态环境进行打分,发现广州省的生态环境得分逐年递增。我们将该评价模型推广至全国,并采用SARIMA的时间序列模型对我国新能源汽车的发展进行预测和分析,从政府政策,企业活力,成本支出,基础设施四个方面解释说明影响我国新能源汽车发展的因素,进而验证新能源汽车的发展对我国生态环境的影响,我们发现新能源汽车的发展有利于我国生态环境的改善。
Since 2011, with the government’s support and encouragement, new energy vehicles have rapidly developed in China. They have transitioned from policy-driven to market-driven development, and their impact on the ecological environment should not be underestimated. This study clusters and categorizes the development levels of new energy vehicles in different provinces of China. Guangzhou province, which represents the case study, is selected. We use SO2, NOx, and industrial smoke (particulate matter) as indicators for the impact of new energy vehicles on the ecological environment. We employ the TOPSIS entropy weight method to score the ecological environment based on a time series from 2007 to 2021 and find an increasing trend in the ecological environment score in Guangzhou province over the years. We extend this evaluation model to the national level and use the SARIMA time series model to forecast and analyze the development of new energy vehicles in China. We explain and validate the factors influencing the development of new energy vehicles in China from four aspects: Government policies, business vitality, cost expenditure, and infrastructure. Subsequently, we verify the impact of the development of new energy vehicles on China’s ecological environment, we find that the development of new energy vehicles is conducive to the improvement of China’s ecological environment.

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