Research on optimal combination model for forecasting traffic accident

doi:10.16265/j.cnki.issn1003-3033.2017.05.006

Abstract

Abstract: To predict death toll caused by traffic accident accurately,a UGM(1,1)-Holt combination forecasting model was built by using the entropy method, and the Markov model was improved by introducing the slide transition probability thinking into it to realize optimization of combination forecasting. Finally, Hubei traffic accident death toll in 2012-2014 was predicted, and a comparison of 4 models' predicted values with the measured value was made. The results show that mean relative error(MRE) of the optimal combination forecasting model's fitted value is further reduced to 0.451 0%, MRE of predicted values of 2012-2014 reduced to 1.25%, and that the model can gain advantages of the single models, and can ensure greater prediction accuracy.

Key words: traffic accident, death toll, entropy method, optimal combination forecast, Markov

CLC Number:

X951

SONG Yinghua, CHENG Lingxi , LIU Dan, LYU Wei. Research on optimal combination model for forecasting traffic accident[J]. China Safety Science Journal, 2017, 27(5): 31-35.

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