Traffic Flow Forecast Based on Neural Network Ensemble
Shuyan Chen, Wei Wang · Journal of Highway and Transportation Research and Development · 2004
Neural Network ensemble is firstly applied to forecast traffic flow,which can improve remarkably the generalization ability of learning systems through training several neural networks and then combining their results.Based on Boosting and Bagging,the method of neural network ensemble with the strategy of divide and conquer is proposed,and the assignment algorithm of sub-neural networks weight coefficients is also discussed.The above-mentioned three models are employed to forecast traffic flow of an intersection in Suzhou city with favor resul.The experiments show that neural network ensemble method is better than simplex neural network,and traffic flow forecasting based on neural network ensemble is valid and feasible.