Prediction of Resumed Production Trajectories in the Post-Epidemic Area Based on Big Power Data

Before the Spring Festival of 2020, China began to spread the new 2019-ncov coronavirus, and the outbreak period coincides with the Spring Festival. The ability to resume production of post-epidemic after the festival has become the focus of attention. This paper proposes an improved forecasting method for resumption based on big data and trajectory clustering. This method clusters the daily power consumption patterns of different industries, summarizes the characteristics of the epidemic situation, and improves the intelligent prediction method. It can evaluate the resumption of production in regional industries and enterprises when there is no clear trend in the external economic environment. It quantitatively solves the problem of forecasting and evaluating the degree of resumption in the context of the epidemic. Calculations are made for the resumption of production in typical industrial agglomeration areas, and the results show that the method can accurately reflect the recovery trend of enterprises and industries from the perspective of feature modification.