目录
摘要Ⅲ
关键词Ⅲ
AbstractⅣ
引言
1绪论1
1.1研究背景 1
1.2研究意义 1
1.3国内外研究现状1
1.3.1国内研究现状1
1.3.2国外研究现状2
1.4研究内容2
1.5技术路线3
2方法原理3
2.1K均值聚类3
2.1.1算法原理3
2.1.2应用领域4
2.2主成分分析4
2.2.1算法原理4
2.2.2应用领域5
3数据来源6
4实验分析6
4.1K均值聚类6
4.1.1数据处理6
4.1.2实验结果7
4.2主成分分析10
4.2.1数据处理10
4.2.2实验结果10
5结果分析12
6讨论与结论12
致谢13
参考文献13
附录1 15
附录2 17
图11 环保重点城市空气质量评价技术路线图3
图41 各类成员及聚类变量均值变化折线图9
表41 各指标二级标准值6
表42 各城市所属类别7
表43 最终类中心表8
表44 重点城市空气质量分布表9
表45 主成分分析结果10
表46 主成分载荷矩阵11
表47 第一主成分得分表11
基于聚类分析和主成分分析的重点城市空气质量评价
摘 要
近年来，我国不断推进和加快了城市化和现代工业化的脚步，城市经济在快速增长的同时却也造成了严重的空气污染和环境问题。目前全国仍有很多城市出现了雾霾等空气污染问题，这些污染问题极大地影响了人民的生产生活，同时也威胁着人民的生命健康。因此如何有效的治理空气污染就成了政府要解决的重点民生保障问题。为实现社会的可持续发展，政府逐渐加大在空气治理上的投资，而进行空气治理的首要关键就是对空气质量进行 *51今日免费论文网|www.51jrft.com +Q: &351916072& 
评价，以便有针对性的解决空气污染问题，同时减少不必要的成本。本文以2019年《中国统计年鉴》中2018年环保重点城市空气质量数据为例进行分析，该数据包含113个样本观测值和7个影响因素；首先运用K均值动态聚类法将所有城市的空气质量分为优、较优、良、较差、差5个等级，并计算类间离散程度和类内离散程度的比值来评估聚类效果的好坏；其次用主成分分析提取累积贡献率达85%的主成分，对照主成分的表达式来解释主成分含义，分析出对空气质量影响最大的因素。最终实验结果表明我国大多数城市空气质量较差，其中影响城市空气质量最主要的因素是可吸入颗粒物(PM10)、细颗粒物(PM2.5)，因此政府应针对两个因素制定环境治理措施。
AIR QUALITY ASSESSMENT OF KEY CITIES BASED ON CLUSTER ANALYSIS AND PRINCIPAL COMPONENT ANALYSIS
ABSTRACT
In recent years, China has continuously promoted and accelerated the pace of urbanization and modern industrialization. The rapid growth of the urban economy has also caused serious air pollution and environmental problems. At present, there are still many cities in the country that have air pollution problems such as smog. These pollution problems have greatly affected peoples production and life, and also threatened peoples lives and health. Therefore, how to effectively control air pollution has become a key issue for peoples livelihood security to be solved by the government. In order to achieve the sustainable development of society, the government gradually increased investment in air governance. Carry out evaluations in order to solve the air pollution problem in a targeted manner while reducing unnecessary costs. This article analyzes the air quality data of key environmental protection cities in 2018 in the "China Statistical Yearbook" in 2019. The data contains 113 sample observations and 7 influencing factors. First, the Kmeans dynamic clustering method is used to analyze the air in all cities. The quality is divided into five grades: excellent, better, good, poor, and poor, and the ratio of the degree of dispersion between the classes and the degree of dispersion within the class is calculated to evaluate the quality of the clustering effect; then the main component analysis is used to extract the cumulative contribution 85% of the main components, according to the expression of the main components to explain the meaning of the main components, analyze the factors that have the greatest impact on air quality. The experimental results show that the air quality of most cities in China is poor, and the most important factors that affect the air quality of cities are inhalable particulate matter (PM10) and fine particulate matter (PM2.5). Therefore, the government should formulate environmental governance measures against these two factors.

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