The quantitative data of logistic demand are the important basis for regional logistic development policy and planning, there are many factors influencing logistic demand, so traditional forecast method can not overall consider all kinds of factors and has lower forecast accuracy. In order to improve the forecast accuracy of logistic demand, combined forecast method is used to set up the combined forecast model based on support vector machines and neural network, firstly support vector machines are used to forecast and forecast basic data are obtained, then residual modification is conducted by BP neural network, and numerical example simulation analysis indicates that combined forecast model has higher accuracy, is a kind of effective forecast model and provides a new idea for logistic demand forecast.