上海空气污染数据统计分析
时间:2019-11-24 21:12 来源:毕业论文 作者:毕业论文 点击:次
| 摘要中国是一个发展中大国，近年来，随着社会经济的不断发展，工业化持续推进，以煤碳为主的能源消耗排放出大量的二氧化硫、氮氧化物、烟尘等大气污染物，同时伴随着机动车流量迅速增加，机动车尾气的排放更加加剧了大气污染。许多研究表明，呼吸道疾病与大气污染息息相关，我国严重的大气污染对居民健康，特别是呼吸道健康造成了巨大的危害。本文以上海市为例，按照 GAM 理论，使用 R 语言建立大气污染数据，气象数据与同期呼吸道疾病患病率之间的统计模型，并对呼吸道疾病患病率进行了预测。目的在于对大气污染与呼吸道疾病的关系形成更为全面客观的认识，并能够预测相应大气污染水平下的呼吸道疾病发病率。42038 毕业论文关键词 呼吸道疾病发病率 大气污染 GAM模型 Title Statistical analysis of air pollution data Abstract China is a developing country. In recent years, with the development of social economy and the boost of industrialization, coal based energy consumption emit a large number of atmospheric pollutant such as2 SO,2 NO and smoke. Meanwhile, with the increase of motor vehicle, the vehicle emissions aggravate the air pollution. Many studies show that respiratory diseases are closely related to air pollution. Our country’s serious air pollution is harmful to the health of the residents, especially the respiratory health. In this paper, taking the respiratory diseases in Shanghai as an example, we established several statistical models based on GAM and predict the incidence by R language. These models considered factors as: the air pollutant data and the meteorological data. The purpose of this paper is to form a more comprehensive and objective understanding of the relationship between air pollutant and respiratory diseases, and to predict the incidence of respiratory diseases at the corresponding levels of air pollution. Keywords Incidence of respiratory diseases Air pollution GAM 目次 1引言1 1.1研究的背景及意义1 1.2文献回顾1 1.3研究思路2 2大气污染的作用机理4 3基本原理5 3.1非参数模型5 3.2广义可加模型（GAM）的基本数学原理5 3.3广义可加模型（GAM）的共曲线性5 3.4广义可加模型（GAM）的建立与求解6 3.5广义可加模型（GAM）的拟合检验7 4上海市呼吸道疾病与大气污染关联的实证分析8 4.1变量选取及数据的预处理8 4.2建立模型12 4.3预测21 4.4模型评估21 4.5模型评价及改进22 结论24 致谢25 参考文献26
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