To forecast ship traffic volume in port or waterway precisely,back propagation(BP) and radial basis function(RBF) neural network forecasting models were established and simulated.

In order to improve inland waterway capacity,the arrival distribution and headway distribution of vessel traffic flow were analyzed.

Numerical simulation technology is used to analyze the effect of the serving efficiency on the vessel traffic flow.

Composite systematic forecasting model and method for vessel traffic flow forecasting;

The traffic flow forecasting model based on neural network has been applied widely in ITS because of its high forecasting accuracy and self-learning ability.

On the basis of analyzing dynamic traffic flow in urban road tunnel, this paper puts forward the dynamic neural network model of the traffic flow forecasting in urban road tunnel, the mode based on the Elman network, with functions of the state memory, time series model established by Elman network is a autoregressive moving average model.

Research of Generalized Neural Network and Its Application in Traffic Flow Forecasting;

Short-term traffic flow prediction method based on SVM;

The paper discusses and researches several methods of traffic flow prediction in the history at home and abroad considering the feature of traffic flow.