Short-Term Traffic Flow Prediction Model of Wavelet Neural Network Based on Mind Evolutionary Algorithm

摘要

This paper introduces mind evolutionary algorithm (MEA) into the application of short-term traffic flow prediction, and proposes a short-term traffic flow prediction model of wavelet neural network based on mind evolutionary algorithm (MEA-WNN). The optimal connection weight and wavelet parameters of wavelet neural network (WNN) are searched globally by MEA, and the convergence capacity of wavelet neural network is improved. The experimental data show that, compared with the prediction model of the traditional WNN and the WNN based on genetic algorithm (GA-WNN), the prediction model of MEA-WNN has higher global prediction accuracy.