Abstract
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.
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