首页> 外文会议>International Symposium on Neural Networks pt.2; 20040819-20040821; Dalian; CN >A Freeway Traffic Incident Detection Algorithm Based on Neural Networks
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A Freeway Traffic Incident Detection Algorithm Based on Neural Networks

机译:基于神经网络的高速公路交通事件检测算法

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摘要

This paper proposes a novel freeway traffic incident detection algorithm. Two stages are involved. First, get the freeway traffic flow model based on BP neural networks and use the model to obtain the output prediction. The residual signals will be gotten from the comparison between the actual and prediction states. Second, a SOM neural networks is trained to classify characteristics contained in the residuals. Hence, based on the classification given by the SOM neural networks, traffic incidents can be detected. Both theory analysis and simulation research show that this algorithm is effective.
机译:提出了一种新型的高速公路交通事故检测算法。涉及两个阶段。首先,获得基于BP神经网络的高速公路交通流模型,并使用该模型获得输出预测。残余信号将从实际状态与预测状态之间的比较中获得。其次,训练SOM神经网络以对残差中包含的特征进行分类。因此,基于SOM神经网络给出的分类,可以检测到交通事故。理论分析和仿真研究均表明该算法是有效的。

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