道路交通事故灰色Verhulst预测模型  

Grey Verhulst Predictive Model of Road Traffic Accidents

作　　者：王福建[1] 李铁强 俞传正[3] 

机构地区：[1]浙江大学交通工程研究所,浙江杭州310027 [2]河北省沧州市交通局,河北沧州061000 [3]浙江省公安厅交通管理局,浙江杭州310007

出　　处：《交通运输工程学报》2006年第1期122-126,共5页Journal of Traffic and Transportation Engineering

基　　金：国家自然科学基金项目(50478082)

摘　　要：为提高道路交通事故灰色预测模型的预测精度,分析了GM(1,1)模型和灰色Verhulst模型的特点,发现GM(1,1)模型适用于具有较强指数规律的序列,只能描述单调的变化过程,而Verhulst模型则适用于非单调的摆动发展序列或具有饱和状态的S形序列。针对近年来中国道路交通事故表现为具有饱和状态的S形过程,建立交通事故Verhulst预测模型。Verhulst预测模型和GM(1,1)预测模型预测的2004年交通事故死亡人数分别为10.87万人和11.72万人,相对误差分别为1.49%和9.43%,可见Verhulst模型的预测精度明显优于GM(1,1)模型。In order to improve the predictive precisions of grey predictive models for road traffic accidents, the properties of GM（1,1） model and grey Verhulst model were analyzed. GM（1,1） model adapted to the sequences with good exponent law, only described monotonous change process, Verhulst model adapted swinging sequences or saturated S-shape sequences. Recently, road traffic accidents in China developed as saturated S-shape sequences, so a Verhulst predictive model of road traffic accidents was put forward. The predictive values of grey Verhulst model and GM（1,1） model for the death people numbers of road traffic accidents in 2004 in China are 108 700 and 117 200 respectively, their predictive precisions are 1.49% and 9.43% respectively, which shows that the predictive precision of the presented model is better than that of GM（1,1） model. 4 tabs, 1 fig, 10 refs.

关 键 词：交通安全 道路交通事故 灰色预测 灰色VERHULST模型 GM(1 1)模型 

分 类 号：U491.31[交通运输工程—交通运输规划与管理]