A Data Processing Algorithm Based on Vehicle Weigh-in-motion Systems

被引：0

作者：

Chen, Nan ^{[1
]}

Li, Quanhu ^{[1
]}

Li, Fei ^{[1
]}

Jia, Zhiliang ^{[1
]}

机构：

[1] Inner Mongolia Univ, Dept Elect & Informat Engn, Hohhot, Peoples R China

来源：

2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC) | 2013年

关键词：

the weigh-in-motion system; BP neural network; genetic algorithm; optimization;

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：

According to the output value of gravitational sensors and speed of vehicles, one back-propagation (BP) neural network model is established. The genetic algorithm is used to optimize the BP neural network. This method can speed up the convergence and avoid getting stuck in the local minimum. The experiment results show that the optimizing BP neural network algorithm based on genetic algorithm can reduce the average error of the calculation and prediction. And the accuracy and efficiency of the weigh-in-motion (WIM) system are improved.

引用

页码：227 / 231

页数：5

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