Industrial coal utilisation efficiency prediction based on Markov Chain Model

Hui-Fang Zhang and Yun-Xia Yang

International Journal of Global Energy Issues, 2023, vol. 45, issue 2, 138-152

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. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijgeni:v:45:y:2023:i:2:p:138-152

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