Research on the Prediction of VNN Neural Network Traffic Flow Model Based on Chaotic Algorithm

Yin Lisheng (Hefei University of Technology)
He Yigang (Hefei University of Technology)
Dong Xueping (Hefei University of Technology)
Lu Zhaoquan (Hefei University of Technology)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 11, No 6: June 2013

This paperresearches on the prediction of traffic flow chaotic time series based on VNNTF neural network. First, the traffic flow time series chaotic feature is extracted by chaos theory. Pretreatment for traffic flow time series and the VNNTP neural networks model was build by this. Second, principles of neural network learning algorithm VNNTF is described. Based on chaotic learning algorithm, the neural network traffic Volterra learning algorithm isdesigned for fast learning algorithm. Last, a single-step prediction of traffic flow chaotic time series is researched by VNNTF network model based on chaotic algorithm. The results showed that the VNNTF network model predictive performance is better than the Volterra prediction filter and the BP neural network   by the simulation results and root-mean-square value. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2664