| 道路交通事故灰色Verhulst预测模型 |
| |
| 引用本文： | 王福建, 李铁强, 俞传正. 道路交通事故灰色Verhulst预测模型[J]. 交通运输工程学报, 2006, 6(1): 122-126. |
| |
| 作者姓名： | 王福建 李铁强 俞传正 |
| |
| 作者单位： | 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 |
| |
| 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。
|
| 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 |
| 文章编号： | 1671-1637(2006)01-0122-05 |
| 收稿时间： | 2005-09-20 |
| 修稿时间： | 2005-09-20 |
Grey Verhulst Predictive Model of Road Traffic Accidents |
| |
| WANG Fu-jian, LI Tie-qiang, YU Chuan-zheng. Grey Verhulst Predictive Model of Road Traffic Accidents[J]. Journal of Traffic and Transportation Engineering, 2006, 6(1): 122-126. |
| |
| Authors: | WANG Fu-jian LI Tie-qiang YU Chuan-zheng |
| |
| Affiliation: | 1. Institute of Transportation Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China;;2. Cangzhou Transportation Bureau of Hebei Province, Cangzhou 061000, Hebei, China;;3. Road Traffic Administration Bureau, Public Security Department of Zhejiang Province, Hangzhou 310007, Zhejiang, China |
| |
| Abstract: | 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. |
| |
| Keywords: | traffic safety road traffic accidents grey prediction grey Verhulst model GM(1 1) model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《交通运输工程学报》浏览原始摘要信息 |
|
点击此处可从《交通运输工程学报》下载全文 |
|
