【摘要】 PM_2.5又称细颗粒物，是大气污染物的主要成分之一，易于富集空气中的有毒重金属、酸性氧化物、有机污染物、细菌和病毒等有害成分，且粒径较小，可以进入人体肺部，进而危害人体健康。研究气象因素对PM_2.5的影响，对于控制PM_2.5，改善空气质量至关重要。为了探究相关影响因素，文章选取了基因表达式编程（GEP）、支持向量回归（SVR）和线性回归（LR）3种具有代表性的智能信息处理方法，利用来自中国12个城市的环境监测数据（2021年1月1日—2021年12月31日），建立了气象因素与PM_2.5之间的定量关系模型。利用相关系数评估各个气象因素的拟合程度，衡量各气象因素对PM_2.5浓度的影响。实验结果表明，气象因素对PM_2.5的影响介于-7.004 7～0.380 1之间；湿度和大气压力对PM_2.5的贡献大于其他气象因素。更多还原

【Abstract】 PM_2.5, also known as fine particulate matter, is one of the main components of atmospheric pollutants. It is prone to accumulate harmful substances such as toxic heavy metals, acidic oxides, organic pollutants, bacteria and viruses in the air, and its particle size is small. Hence, It can enter the lungs, thereby endangering human health. Studying the impact of meteorological factors on PM_2.5 is crucial for controlling PM_2.5 and enhancing air quality. In order to explore influencing factors, the article selected three representative intelligent information processing methods: Gene Expression Programming（GEP）, Support Vector Regression（SVR）, and Linear Regression（LR）. Drawing on environmental data from 12 cities in China（January 1, 2021 to December 31,2021）, a quantitative relationship model was established. Moreover, the correlation coefficients were used to evaluate the fitting degree of various factors and measure their impact on PM_2.5 concentration. The results indicate that the influence of meteorological factors ranges from-7.004 7 to 0.380 1; The contribution of humidity and atmospheric pressure is greater, among other factors.更多还原