Optimization SVR fog prediction model based on genetic algorithm

doi:10.3969/j.issn.1000-1565.2016.03.014

Abstract

Abstract: To perform smog forecast,this paper puts forward a model,which is based on support vector regression(SVR)method and GA method.The first eigenvector dimension is reduced using factor analysis,and the SVR parameters are optimized through the GA method,and put into the SVR model for the prediction of the PM2.5 value of the city of Baoding.Through comparison, an optimized prediction model is obtained.

Key words: PM2.5 forecast, SVR, factor analysis, GA method

CLC Number:

TP183

ZONG Xiaoping,WU Zihan,LIU Yan. Optimization SVR fog prediction model based on genetic algorithm[J]. Journal of Hebei University (Natural Science Edition), 2016, 36(3): 307-311.

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