Combination Prediction Of Fresh Agricultural Products Logistics Demand In Shaanxi Province Based On Shapley Value

Shaanxi province is an important area for cold chain logistics layout planning of fresh agricultural products in China.Despite massive scale of fresh agricultural product logistics in Shaanxi province,there are still many problems and also lacking of intuitive and effective data to support.In order to ensure higher logistics efficiency and economic benefits,and avoid the waste of resources due to insufficient or excessive logistics supply,this thesis combined with theoretical and empirical research to predict the logistics demand of fresh agricultural products in Shaanxi Province,in the meanwhile,this thesis put forward suggestions and made plan for the development of logistics in Shaanxi Province.(1)Aiming at the imperfect prediction index system of fresh agricultural products logistics demand,combined with literature and the situation of Shaanxi province logistics industry development,logistics demand factors would be analyzed from four aspects,which were the level of economic development,industrial structure,human factors and logistics development scale level.The four aspects would be expanded into 13 secondary indicators.Considering the acceleration of urbanization,the total consumption of fresh agricultural products of urban residents was taken as the measurement index of fresh agricultural products logistics demand prediction.In order to explore the correlation between the influencing factors and the total consumption of fresh agricultural products,this thesis selected six influencing factors by GRA,which correlation coefficient were above 0.8 as explanatory variables.(2)In view of the research status quo of immature statistical prediction model of demand for fresh agricultural products logistics in Shaanxi province,this thesis used data in the Statistical Yearbook of Shaanxi Province from 2005 to 2018.From the perspective of Multiple Linear Regression,Grey Forecast,Nonlinear Intelligent Forecast,this thesis selected Principal Component Regression Model,Multi-variable Grey Model and Radial Basis Function neural network model respectively for predicting.For the perspective of Nonlinear Intelligent forecast,this thesis proposed the unbiased gray theoretical forecast model of RBF neural network.The GM(1,1)model was unbiased modified by introducing parameters.In order to further enhance the smoothness of data and reduce randomness,the power function was used to transform the original data.Then,the prediction accuracy of GM(1,1)model was compared with the unbiased GM(1,1)model,and the results showed that the accuracy of unbiased GM(1,1)model was more optimal for sequence data forecast.At the same time,combined the unbiased GM(1,1)model with the high approximation ability of RBF neural network,this thesis proposed an improved unbiased Grey-RBF Neural Network model,and the prediction error MAPE was controlled below 5%.The optimization of RBF Neural Network input data made the prediction results more accurate and greatly improved its applicability in the demand prediction of fresh agricultural products logistics in Shaanxi Province.Finally,in order to reduce the prediction error of single model,Shapley value was introduced for model combination,and the rationality of error distribution was greatly improved through the determination of weight for achieving the effect of optimal combination.The prediction results showed that the combined model could predict the demand of fresh agricultural products logistics in Shaanxi province with high precision,and the predicted value was closest to the real value.Based on the prediction of single model,the prediction accuracy based on Shapley value combined model was further improved.(3)In view of the problems existing in the development of cold chain logistics industry of fresh agricultural products in Shaanxi Province,according to the prediction results,the thesis provided theoretical basis and suggestions for cold chain logistics industry in Shaanxi Province,relevant departments could carry out reasonable construction of fresh agricultural cold chain logistics according to the prediction results,so that it could adapt to the diversified needs of fresh agricultural products in Shaanxi Province.