Chaos Rapid Recognition of Traffic Flow by Using Rough Set Neural Network

The rapid recognition problem of chaos in traffic flow was studied by using rough set neural network. Based on analyzing the demand of intelligent transportation system and the problems of the exiting recognition methods of chaos in traffic flow, the intelligent recognition method of chaos was proposed. The principle and the structure of the system are briefly introduced. There are online recognition subsystem and offline recognition subsystem mainly. Normal methods are used in the offline recognition model. The online recognition model was established by using rough set neural network, which the wavelet packet energy features vector of the anterior time series of traffic flow were used as original features vector.The recognizing rules and the reduced features vector of the chaos were acquired by using rough set theory. The reduced features vector was used as the input variables of the online recognition neural network model. The simulation result shows its correctness.