Research on algorithms of grey residual error model in highway traffic accidents forecast

被引：0
|
作者：
Li, G [1 ]
Huang, XY [1 ]
Liao, SL [1 ]
Han, FQ [1 ]
Yuan, RD [1 ]
机构：
[1] Chongqing Univ, Coll Automat, Chongqing 630044, Peoples R China
来源：
Wavelet Analysis and Active Media Technology Vols 1-3 | 2005年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
By analyzing the procedure to establish Gray Residual Error Model(GREM), this paper classifies the factors that affect the forecast results with GREM, such as objects being amended, data being selected and methods for data pretreatment. Furthermore, several algorithms of GREM are presented, followed with highway traffic accidents forecast examples. Results indicate that errors will be greatly reduced by these methods in accident forecast, which has great randomicity as well as certain trend. Especially, the method that adopts residual error to establish GREM directly and recover once, has lower complexity, less error, more preferable effect and can be used in practice.
引用
收藏
页码：675 / 682
页数：8
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