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基于神经网络的城市交通流预测

于 2020-12-03 发布
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神经网络可以很好的解决交通领域内的非线性问题,其中前向型神经网络特别适合对交通流的预测。由于神经网络在训练速度和预测精度等方面不断的提高,把神经网络用于建设智能交通体系成为了一种非常明智的选择。人工神经网络模型是在交通流预测领域里很有潜力的一种模型。鉴于此,本文提出了一种基于神经网络的交通流量动态预测模型,分别采用BP神经网络和径向基网络(RBF)建立了预测模型,并给出了数据预处理方法和预测模型评价指标

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