Research On Logistics Demand Forecasting For Jiang Xi Province Based On Multiple Regression And Neural Networks

Regional economy is closely related to the development of regional logistics.A sound logistics system provides guarantee for economic development.Continuous and stable economic growth promotes the maturity and efficiency of the logistics industry.Logistics and the economy are interconnected and promote each other.As a province with a large population and large resources in the central region,the economic rise of Jiangxi Province is a vital part of the country's implementation of the central rise strategy.Economic development is inseparable from the support of logistics,and reasonable logistics planning is the key to the efficient operation of the logistics system.Forecasting regional logistics demand in advance is the basis of regional logistics planning.Establishing a scientific forecasting system can better understand the logistics market demand.It is the purpose of this article to reveal the relationship between logistics development and economic development,accurately predict logistics demand,and provide references for policy formulation and logistics planning.This article combines theoretical research with empirical research,analyzes the current status of logistics and economic development in Jiangxi Province,studies the main factors affecting logistics demand in Jiangxi Province,and selects multiple regression and neural networks as prediction methods to make reasonable predictions for logistics in Jiangxi Province.At the same time,it further reveals the relationship between logistics and economic development,and analyzes the validity of related prediction results,providing a basis for the logistics system planning of Jiangxi Province in a certain period of time in the future.This article first studies the relevant literature of logistics demand forecasting,then introduces the relevant theoretical models,multiple regression models,and neural network models,including the principles and algorithms of these two models,and explains the application of multiple regression and neural networks to logistics demand forecasting.Feasibility.Secondly,the indicator system of the logistics demand forecasting system of Jiangxi Province was constructed,the economic and logistics development status of Jiangxi Province was analyzed,and the influencing factors of logistics demand forecasting of Jiangxi Province were explored.Through comparison and analysis,representative indicators were selected for Our logistics demand forecasting system collects and arranges reliable historical data,performs correlation analysis between indicators,and finally obtains a reasonable forecasting index system.Thirdly,using the multiple regression model and BP neural network model for matureapplication in the forecasting field,the empirical research is conducted on the logistics market in Jiangxi Province,and statistical data mining tools such as SPSS and MATLAB are used to establish the data based on the relevant data of the economy and logistics market in Jiangxi Corresponding models,meanwhile,the models and methods of logistics market demand forecasting based on multiple regression and BP neural network theory are discussed.The two models of logistics market demand forecasting models and methods are analyzed separately.Finally,after analyzing the prediction results of two different prediction methods,it was found that it basically accorded with the actual situation of logistics development in Jiangxi Province.This shows that the logistics market forecasting model established in this paper is meaningful,the theoretical analysis in this paper is sufficient,and the forecasting analysis has practical value.