Highway traffic prediction with neural network and genetic algorithms

WangYan, Wang Hua, Xiang Limin
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引用次数: 7

Abstract

Traffic prediction method and the correctness of its result are very important for vehicle management, so highway traffic prediction method has a close relationship with vehicle safety. Traditional prediction method has some problems, such as low accuracy and efficiency, so we present a model based on the combination of genetic algorithms and artificial neural network, and by improving these two algorithms in the process of implementation, increase further the accuracy and efficiency of the model. At last, some experiments are made to prove its fine performance.
基于神经网络和遗传算法的公路交通预测
交通预测方法及其结果的正确性对车辆管理至关重要,因此公路交通预测方法与车辆安全有着密切的关系。传统的预测方法存在精度低、效率低的问题,本文提出了一种基于遗传算法和人工神经网络相结合的预测模型,并在实现过程中对这两种算法进行改进,进一步提高了模型的精度和效率。最后通过实验证明了该方法的优良性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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