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Software design and implementation of large-scale intelligent traffic monitoring system

机译:大型智能流量监控系统的软件设计与实现

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The design method of large-scale intelligent traffic monitoring system is studied. Traffic monitoring methods have become the core problem of intelligent transportation research field. To this end, this paper proposes an intelligent traffic monitoring method based on clustering RBF neural network algorithm. Fourier coefficient normalization method is used to extract the feature of traffic state, to be as the basis for intelligent traffic monitoring. Using clustering RBF neural network algorithm identify the traffic state effectively, thus to complete the state recognition of intelligent traffic monitoring. Experimental results show that the proposed algorithm performed in intelligent traffic monitoring, can greatly improve the accuracy of monitoring.
机译:研究了大规模智能交通监控系统的设计方法。交通监测方法已成为智能交通研究领域的核心问题。为此,本文提出了一种基于聚类RBF神经网络算法的智能流量监测方法。傅里叶系数归一化方法用于提取交通状态的特征,作为智能流量监控的基础。使用聚类RBF神经网络算法有效地识别流量状态,从而完成了智能流量监控的状态识别。实验结果表明,在智能流量监测中进行的该算法可以大大提高监测的准确性。

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