宿州学院学报2024，Vol.39Issue(12)：42-46,5.DOI:10.3969/j.issn.1673-2006.2024.12.008
基于改进灰色马尔科夫模型煤矿事故次数预测研究
Research on Predicting the Number of Coal Mine Accidents Based on Improved Grey Markov Model
摘要
Abstract
To accurately predict the number of coal mine accidents,a thorough analysis is conducted on the applica-bility and practicality of traditional grey models,unbiased grey models,and equidimensional new information un-biased grey models in the field of coal mine accident prediction.Firstly,the prediction accuracy of the three models was analyzed using three indicators:mean squared error ratio,small error probability,and average relative error;then,the Markov model is used to optimize and correct the optimal grey model prediction results;finally,the revised grey model is used to predict the number of coal mine accidents from 2024 to 2026.The results showed that after comparing and analyzing the prediction accuracy of traditional grey models,unbiased grey models,and equidimen-sional unbiased grey models,it was found that the equidimensional unbiased grey models exhibited the best predic-tive performance in prediction;the prediction accuracy of the unbiased grey model with equal dimensional innovation is 86.3%.After introducing the Markov model for correction,the prediction accuracy has increased to 94.8%,and the optimized model has a more accurate prediction result.The equal dimensional new information unbiased grey Markov model predicts that the number of coal mine accidents in China will continue to decline in the next three years.关键词
煤矿事故/灰色模型/无偏灰色模型/等维新息无偏灰色模型/马尔科夫模型Key words
Coal mine accident/Grey model/Unbiased grey model/Equal dimensional new information unbiased grey model/Markov model分类
矿业与冶金引用本文复制引用
江善超,张树川..基于改进灰色马尔科夫模型煤矿事故次数预测研究[J].宿州学院学报,2024,39(12):42-46,5.基金项目
安徽省教育厅自然科学研究重点项目(KJ2018A0099) （KJ2018A0099）
安徽省省级研究生线上线下混合示范课程(2022hhsfkc021). （2022hhsfkc021）
