The invention discloses a traffic state prediction method based on the chaos theory and a device thereof. The traffic state prediction method comprises the steps that data stream of traffic roads are acquired so that time sequences of multiple traffic parameters are obtained; multi-parameter phase space reconstruction is performed according to the time sequences of the traffic parameters and multi-parameter phase space is obtained, and optimal fusion of phase points is performed through combination of the Bayes estimation theory in the multi-parameter phase space so that fused phase space corresponding to the multiple traffic parameters is obtained; chaos analysis is performed on the time sequences in the fused phase space, and chaos prediction is performed on the traffic roads through combination of an RBF neural network when the time sequences of the fused phase space present chaos characteristics through analysis. Compared with a conventional single-parameter time sequence prediction method, a better prediction effect can be acquired by the traffic state prediction method so that predictability and precision of the traffic state prediction method are relatively high.
Traffic state prediction method based on chaos theory and device thereof
2015-10-14
Patent
Electronic Resource
English
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