Short-term traffic flow prediction based on incremental support vector regression

被引：0
|
作者：
Su, Haowei [1 ]
Zhang, Ling [1 ]
Yu, Shu [1 ]
机构：
[1] South China Univ Technol, Coll Comp Sci & Engn, Guangzhou 510640, Peoples R China
来源：
ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 1, PROCEEDINGS | 2007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：
In this paper, a new short-term traffic flow prediction model and method based on incremental support vector regression (ISVR) is proposed, according to the data collected sequentially by the probe vehicle or loop detectors, which can update the prediction function in real time via incremental learning way. As a result, it is fitter for the real engineering application. The ISVR model was tested by using the I-880 database and the result shows that this model is superior to he back-propagation neural network (BPNN) model.
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收藏
页码：640 / +
页数：2
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