Research on Markov Prediction Model of Urban Energy Consumption Structure Based on Library Big Data

Energy is an important driving force for the social and economic development. However, with the development of the industrial revolution and the world economy, the energy crisis is becoming more and more serious, and with the increasing greenhouse effect, the pressure of emission reduction in the world is rising. Using the Markov model, the Qingdao city is taken as an example to select coal, oil, natural gas and electricity consumption, and to establish unconstrained programming. The prediction model of energy consumption structure is used to predict the consumption structure of primary energy in China cities, and suggestions on how to adjust the energy structure are given based on the prediction results.