By use of time series and neural network the short-term wind speed forecasting is researched in which the time series model is used to select the input variables and multi-layer back propagation neural network and generalized regression neural network are used to conduct forecasting.

The existing traffic forecasting models are analyzed,and a new short-time forecasting model based on chaos theory is developed.

Available parking space occupancy change characteristics and short-term forecasting model;

Using forecasting algorithms in the traffic flow short-term forecasting system to analyze traffic data and predict the traffic flow condition in short time so as to adopt some relevant traffic controlling and guiding measures.

At the same time, the short-term prediction of real-time traffic flow is key to realize the traffic control and route guidance.