Grey BP Neural Networks Model based on GA and Its Application in Regional Logistics Demand Forecasting

Regional logistics demand is closely related with the regional economic development level. The scale of area economy, the industrial structure, purchasing power and the number of Internet shopping are major economic factors which influence regional logistics demands. This paper chooses the freight volume as the content of logistics demand. Selecting the economic data of Fujian province in 1997—2009 as a panel data and using the grey neural network model based on the genetic algorithm to predict the regional logistics of Fujian province. The empirical results show that: online shopping level is an important influence factor for regional logistics demand; combination forecast model has better prediction effect than single forecasting model; Logistics Demand in Fujian province is on the rise the next few years. The empirical results provide instructive suggestions for the regional logistics demand forecast.