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Highway traffic prediction with neural network and genetic algorithms

机译:基于神经网络和遗传算法的高速公路交通量预测

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摘要

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.
机译:交通预测方法及其结果的正确性对于车辆管理非常重要,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,效率低等问题,因此提出了一种基于遗传算法和人工神经网络相结合的模型,通过在实现过程中对这两种算法进行改进,进一步提高了预测的准确性和效率。该模型。最后,进行了一些实验以证明其良好的性能。

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