Assessing Dynamic Neural Networks for Travel Time Prediction

被引：0
|
作者：
Shen, Luou [1 ]
Huang, Min [2 ]
机构：
[1] S China Univ Technol, Sch Civil & Transportat Engn, Guangzhou 510641, Guangdong, Peoples R China
[2] Wuhan Inst Technol, Sch Environm & Civil Engn, Wuhan 430073, Peoples R China
来源：
APPLIED INFORMATICS AND COMMUNICATION, PT I | 2011年 / 224卷
关键词：
Advanced Traffic Information System; Travel Time Prediction; Detector Data; Dynamic Neural Networks; PERFORMANCE; FRAMEWORK;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Ularly suitable for predicting variables like travel time, but has not been adequately investigated. This study compares the travel time prediction performance of three dynamic neural network topologies with different memory settings. The results show that the time-delay neural networks out-performed the other two topologies. This topology also performed slightly better than the multilayer perceptron neural networks.
引用
收藏
页码：469 / +
页数：3
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