Study on Probability Estimation of Haze in Beijing Based Logistic Regression Model - Journal of Geoscience and Environment Protection

GEP > Vol.5 No.6, June 2017

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

HTML XML

Download as PDF (Size: 199KB) PP. 37-41

DOI: 10.4236/gep.2017.56005 2,890 Downloads 3,758 Views Citations

Author(s)

Yonghua Zhu, Tian Zhang, Chenglin Chen

Affiliation(s)

North China Electric Power University, School of Mathematics and Physics, Beijing, China.

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.

KEYWORDS

Haze, Logistic Regression, Season, Relative Humidity

Share and Cite:

Zhu, Y. , Zhang, T. and Chen, C. (2017) Study on Probability Estimation of Haze in Beijing Based Logistic Regression Model. Journal of Geoscience and Environment Protection, 5, 37-41. doi: 10.4236/gep.2017.56005.

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journals Menu

Home

About SCIRP

Service

Policies