Research on Logistics Demand Prediction in Liaoning Province Based on BP Neural Network
Logistics demand forecasting plays an important role in economic development.Selecting 7 economic indicators influencing factors from 2004 to 2021 in Liaoning Province as input indicators,and cargo transportation volume as output indicators of logistics demand,MATLAB R2022b software was used to predict logistics demand in Liaoning Province.Using the grey correlation analysis method,the correlation degree of the influencing factors of economic indicators was analyzed.Based on the results,it is believed that there is a strong correlation between input indicators and output indicators.Subsequently,a logistics demand prediction model was constructed based on the BP neural network method.After simulation and prediction,it is found that the BP neural network model is effective in predicting logistics demand.
BP neural networkregional economygrey correlation analysislogistics demand forecasting
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