Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (24): 11-15.

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Road traffic accidents prediction based on optimal weighted combined model

ZHAO Ling1,2, XU Hongke1, CHENG Hongliang1   

  1. 1.School of Electronic and Control Engineering, Chang’an University, Xi’an 710064, China
    2.School of Communication & Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
  • Online:2013-12-15 Published:2013-12-11

基于最优加权组合模型的道路交通事故预测

赵  玲1,2,许宏科1,程鸿亮1   

  1. 1.长安大学 电子与控制工程学院,西安 710064
    2.西安邮电大学 通信与信息工程学院,西安 710121

Abstract: The prediction of traffic accident is the basis of transportation safety, assessment and decision-making. Aimed at solving the limitations in various single grey forecasting methods, a combined forecasting model of road traffic accidents based on optimal weighted method is put forward. According to the characteristics of traffic accident in China, a model combining GM(1,1), Verhulst and SCGM(1,1)c is established and the weight coefficients of combined forecasting model are determined by optimal weighted method. The deaths of traffic accident in China from 2001 to 2007 are taken as original data to establish forecasting model predicting the deaths of traffic accident from 2008 to 2010. The results demonstrate that the forecast accuracy of combined model is better than that of GM(1,1)model,Verhulst model and SCGM(1,1)c model.

Key words: transportation security, traffic accident, optimal weighted, combined forecasting

摘要: 交通事故预测是交通安全评价、规划和决策的基础。针对各种单一灰色预测模型存在的局限性,建立了一种基于最优加权的灰色组合预测模型。根据我国道路交通事故的发展情况,建立了GM(1,1)、Verhulst和SCGM(1,1)c相结合的组合预测模型,运用最优加权法确定组合预测模型的权重系数。利用2001—2007年我国道路交通事故死亡人数的实际值作为原始数据,构建各个单一预测模型和最优组合预测模型,预测其2008—2010年交通事故死亡人数。预测结果表明,组合预测模型比单一GM(1,1)模型、Verhulst模型和SCGM(1,1)c模型具有更高的预测精度。

关键词: 交通安全, 交通事故, 最优加权, 组合预测