Title: Industrial coal utilisation efficiency prediction based on Markov Chain Model

Authors: Hui-Fang Zhang; Yun-Xia Yang

Addresses: Department of Mathematics, Xinzhou Teachers University, Shanxi, Xinzhou, China ' Department of Big Data and Intelligent Engineering, Shanxi Institute of Engineering and Technology, Shanxi, Yangquan, China

Abstract: In order to solve the problems of high error interval band width, low-prediction accuracy and long prediction time in traditional methods, an industrial coal utilisation efficiency prediction method based on Markov Chain Model is proposed. Based on the combination of probability matrix and Markov Chain, the prediction model of industrial coal utilisation efficiency is constructed. The grey GM[1,1] method was used to optimise, adjust and modify the model, and the relevant data of industrial coal utilisation were input into the model, and the prediction results of industrial coal utilisation efficiency were obtained. Experimental results show that the error interval band width value of this method is 0.07, and the prediction accuracy of industrial coal utilisation efficiency is up to 95%. Only 4 s can predict the coal utilisation efficiency of 30 different regions, indicating that this method has high-prediction accuracy and good application effect.

Keywords: Markov chain model; industrial coal; utilisation efficiency; prediction model design.

DOI: 10.1504/IJGEI.2023.129507

International Journal of Global Energy Issues, 2023 Vol.45 No.2, pp.138 - 152

Received: 18 Feb 2022
Accepted: 31 May 2022
Published online: 10 Mar 2023 *

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