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基于我国民用汽车拥有量的主成分分析
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Abstract:
随着我国社会主义现代化的建设蓬勃发展、国民经济良好增长,越来越多人们的买车需求加大。本文基于主成分分析法,对民用汽车拥有量进行定量分析,并对未来民用汽车拥有量进行总体趋势预测。我国民用车辆的拥有量,由量变到质变地影响民用交通规划,使得汽油消耗且大量尾气排除,既消耗不可再生资源又影响空气质量。则根据目前民用汽车拥有量的分析,进行汽车数量控制,制定相适应地环境保护政策,不可再生资源的合理规划。根据未来民用汽车拥有量进行总体趋势预测,可提前做好应对措施。故该分析对民用交通规划、环境保护政策、不可再生资源的合理规划、汽车数量管控,都有着举足轻重的意义。
With the vigorous development of China’s socialist modernization construction and the good growth of the national economy, more and more people have increased their demand for cars. Based on the principal component analysis method, this paper quantitatively analyzes the ownership of civil vehicles and predicts the overall trend of future civil automobile ownership. The ownership of civil vehicles in China affects civil transportation planning from quantity to quality, so that gasoline consumption and a large number of exhaust gas are eliminated, which not only consumes non-renewable resources but also affects air quality. According to the current analysis of civil automobile ownership, the number of vehicles is controlled, appropriate environmental protection policies are formulated, and reasonable planning of non-renewable resources is formulated. According to the overall trend forecast of future civilian car ownership, countermeasures can be taken in advance. Therefore, the analysis is of great significance to civil transportation planning, environmental protection policies, rational planning of non-renewable resources, and control of the number of vehicles.
[1] | 王英, 胡晓华. 中国民用汽车拥有量多层面分析[J]. 海南师范大学学报(自然科学版), 2018, 31(2): 206-210. |
[2] | 陈永胜, 周林芳. 基于指数平滑法与马尔科夫链的汽车拥有量预测模型[J]. 长春工程学院学报(自然科学版), 2020, 21(1): 124-128. |
[3] | 刘一鹤, 牟唯嫣, 金童. 线性回归方法在空气质量影响因素分析中的应用[J]. 应用数学进展, 2022, 11(8): 5936-5950. |
[4] | 曲培元, 赵志斌, 陈浩, 徐东昕, 刘国军. 基于多元线性回归分析方法的汽车油耗(MPG)预测模型[J]. 统计学与应用, 2022, 11(2): 206-215. |
[5] | 党耀国, 米传民, 钱吴永. 应用多元统计分析[M]. 北京: 清华大学出版社, 2012: 112-146. |
[6] | 于淼, 金童. 基于主要城市中主要污染物排放量的主成分分析(英文) [J]. 农业科学与技术: 英文版, 2017, 18(7): 1260-1262. |
[7] | 金童, 牟唯嫣, 贾晓芳, 李泽妤. 基于因子分析法的我国邮政和电信业务量情况分析[J]. 统计学与应用, 2021, 10(6): 989-996. |
[8] | 国家统计局, 编. 中国统计年鉴2021 [EB/OL]. http://www.stats.gov.cn/tjsj/ndsj/2021/indexch.htm, 2021-09. |
[9] | 何晓群. 多元统计分析(第四版) [M]. 北京: 中国人学出版社, 2015: 113-127. |