Real-time Optimal Control of Traffic Flow Based on Fuzzy Wavelet Neural Networks

被引：0
|
作者：
Guan, Hai-shuang [1 ]
Ma, Wen-ge [2 ]
Wang, Qiu-ping [3 ]
机构：
[1] Beihua Univ, Coll Elect & Informat Engn, Beijing 132021, Jilin, Peoples R China
[2] Liaoning Univ Technol, Grad Sch, Jinzhou 121001, Peoples R China
[3] Northeast Dianli Univ, Jilin 132012, Taiwan
来源：
ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 2, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/ICNC.2008.375
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The forecast of real-time traffic flow is one of important contents of intelligent transportation system research. Based on the related knowledge of wavelet analysis and fuzzy neural networks, this paper proposes the fuzzy wavelet neural networks control method. It takes wavelet function as fuzzy membership function, uses neural networks to realize fuzzy reasoning, and finishes the estimate of next cyclical traffic flow. Simultaneously the genetic algorithm is used to optimize the overall network. After the field data test, this method is high precise, stable and compatible.
引用
收藏
页码：509 / +
页数：2
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