Constructing the Industrial Prosperity Index Based on Big Data of Enterprise Electricity

Abstract

This paper is mainly based on the big electric power data of 5900 industrial enterprises above designated size in Shanghai. By combining a complex network and a hidden Markov model, the prosperity index of 164 medium-sized industries in Shanghai is constructed. Specifically, we use complex networks to describe the correlation between different industries, in order to mine the upstream and downstream drivers that affect industrial power consumption, and on this basis, consider the external factors that affect power consumption to establish a hidden Markov model that predicts changes in power consumption in the industry. Further, we use the state probability output by the Hidden Markov Model to define the industrial prosperity index, hoping that the index can fully reflect the economic operation of various industries in Shanghai and become a “barometer” and “wind vane” for economic development.