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Macro Prediction of Traffic Accident in Beijing Based on Model GM (1, N)

机译:基于GM(1,N)模型的北京市交通事故宏观预测

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The factors which affect the occurrence of traffic accidents are very complicated and of great uncertainty. There is some relationship between various influence factors of traffic accidents. Some influence factors dominate the development trends of traffic accidents. This paper uses the method of grey relational analysis to deal with the statistical data of traffic accidents in Beijing from 2002 to 2009. We select nine influence factors of traffic accidents for analysis, and find four influence factors, including number of trucks, total population, total length of highways, and number of large motor vehicles with higher grey relational grade, and set up the macro prediction model GM(1,N). Then the prediction result is undesirable and the probable reason is that the variation tendency of the influence factors is opposed to the variation tendency of traffic accidents.
机译:影响交通事故发生的因素非常复杂,不确定性很大。交通事故的各种影响因素之间存在一定的关系。一些影响因素主导了交通事故的发展趋势。本文采用灰色关联分析的方法对北京市2002年至2009年的交通事故统计数据进行处理。选择9个交通事故影响因素进行分析,找出卡车数量,总人口,建立公路总长,灰色关联等级较高的大型机动车数量,并建立了宏观预测模型GM(1,N)。那么预测结果是不理想的,可能的原因是影响因素的变化趋势与交通事故的变化趋势相反。

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