Research On Regional Cold Logistics Demand Forecasting Based On Combination Model

In recent years,with the continuous and efficient development of China ’s economy,people ’s requirements for material life have also entered a higher stage.The output and demand of fast-moving consumer goods such as fresh agricultural products have increased year after year,and consumers pay special attention to the safety and quality of such food.Therefore,on the basis of the existing fresh agricultural product supply system,how to ensure reasonable resource allocation and high-quality logistics production activities in the region has become a key issue to promote the development of the current cold chain logistics industry and regional economic upgrading.Shanxi Province,as a province with unique geographical features and natural environment in the central part of northern China,although its main types of fresh agricultural products are not complicated,and the scale and system of logistics are not particularly large,there are many unreasonable allocation problems and lack of systematic basic data for research and planning.Therefore,in order to better improve the regional fresh agricultural products logistics system,meet the people ’s growing material life needs,and achieve regional economic growth,after fully analyzing the influencing factors of cold chain logistics in Shanxi Province,this paper chooses to reasonably predict the demand for cold chain logistics composed of specific fresh agricultural products,and finally puts forward plans and suggestions based on this prediction result.In order to realize the prediction of regional cold chain logistics demand,this paper selects the relevant influencing factors of regional cold chain logistics demand after analyzing the main environment.At the same time,the grey correlation method is used to sort the correlation degree of each influencing factor index and select the index,and the influencing factor index system is constructed as the basis for subsequent prediction analysis.Secondly,this study uses relevant data to construct traditional grey model,unbiased grey model and BP neural network model for prediction.Then,in order to reduce the prediction defects caused by the single model algorithm and improve its prediction accuracy,the unbiased GM prediction model and BP neural network model are used to combine and verify the validity according to its prediction working principle.By comparing the prediction results of several models,the results show that the combined model has better fitting and anti-interference,and the prediction results are more accurate.Finally,the combined model is used to reasonably predict the demand for cold chain logistics in Shanxi Province,and the prediction results of the demand for cold chain logistics in Shanxi Province in the next five years are obtained.The results predicted by other models are compared and analyzed to determine the prediction advantages of the combined model.This study fully analyzes the internal and external causes of the development and change of cold chain logistics demand in Shanxi Province,and makes a reasonable prediction of the demand for cold chain logistics in Shanxi Province.The prediction results show that the demand for cold chain logistics in Shanxi Province will increase slowly in the short term.According to the prediction results,by adjusting the distribution of demand in each link of regional cold chain logistics,the further optimization of resource deployment is realized,and the rapid development of regional economy is realized while meeting the needs of people’s material life.