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Study on Probability Estimation of Haze in Beijing Based Logistic Regression Model

机译:基于北京逻辑回归模型雾霾概率估计研究

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摘要

The Logistic Regression Model of two categories is used to explore the relationship between haze and season, various meteorological factors such as air pressure, temperature, relative humidity, precipitation, wind direction and so on. Among all the factors, the relative humidity is best related to haze and season is in the second place. The odds of haze in winter are 17.87 times bigger than that in summer, 3.99 times bigger than that in spring. The odds of haze would increase by 48 percent averagely when the relative humidity increase by 10 percent.
机译:两类物流回归模型用于探索阴霾和季节之间的关系,各种气象因素,如气压,温度,相对湿度,沉淀,风向等。在所有因素中,相对湿度与雾霾和季节最佳。冬季雾霾的几率比夏天更大17.87倍,比春天大3.99倍。当相对湿度增加10%时,雾度的几率平均平均增长了48%。

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