Research on Traffic Flow Prediction Based on Chaos Neural Network Theory

Traffic flow prediction is one of important problem in ITS. Now there are many kinds of algorithm which are based on accuracy and real-time of prediction. In this paper, based on local and add-weight local prediction method of chaos time series, a new kind of prediction algorithm is presented by mix together with their advantage. A unified prediction model can be used for traffic flow forecasting, practical for both condition of local and add-weight local prediction method, but the complexity is not high. Results in experiments shows that it is high accuracy and can be used in traffic flow forecasting.