Research On Regional Logistics Demand Forecasting Method And Case Study

In recent years,with China's regional economic development,optimize industrial structure,people's consumption level enhances unceasingly,and logistics technology progress,logistics has become the important support of economic operation in our country.Some regional logistics industry still exists,however,the unreasonable resources disposition,the cost is high,the service level is relatively low,logistics supply and demand imbalance,and many other problems.For these issues,to accelerate the regional logistics resource integration,optimization of regional logistics network system is the first priority,and forecast regional logistics demand analysis is the important link.Therefore,based on the current analysis of regional logistics demand forecast and the existing problems,this paper chooses the combination of qualitative analysis and quantitative analysis to study the regional logistics demand forecast.The main work is as follows:First of all,based on the principle of the selection of regional logistics demand forecasting index,combining the analysis of various influencing factors of logistics demand,this paper analyzes and selects the regional logistics demand index and regional economic index respectively,and build the index system of regional logistics demand forecasting,Providing the necessary foundation and prerequisite for the construction of the regional logistics demand forecasting model.Secondly,based on the analysis of prediction method and prediction model,combining the characteristics of regional logistics demand forecasting,puts forward the advantage of BP neural network prediction,and on the basis of basic BP neural network prediction model,using the combination model principle,build the grey BP neural network prediction model and grey genetic BP neural network prediction model.Finally,based on the analysis of Shandong economy and logistics development status,BP neural network prediction model,gray BP neural network prediction model and genetic gray BP neural network model are studied in turn,having verified the fit and stability of each prediction model.And through the comparison and analysis,it is concluded that performance of genetic grey BP neural network prediction model is the best,and then,this prediction model is selected to forecast the logistics demand of Shandong Province in the next five years.