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Sun, W. and Sun, J.Y. (2016) Daily PM 2.5 Concentration Prediction Based on Prin-cipal Component Analysis and LSSVM Optimized by Cuckoo Search Algorithm. Journal of Environmental Management, 188, 144-152. https://doi.org/10.1016/j.jenvman.2016.12.011

has been cited by the following article:

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

  AUTHORS: Yonghua Zhu, Tian Zhang, Chenglin Chen

  KEYWORDS: Haze, Logistic Regression, Season, Relative Humidity

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.5 No.6, June 12, 2017

  ABSTRACT: 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.