基于改进GM(1,1)-Markov模型的国内生产安全事故预测研究

doi:10.3969/j.issn.1007-7375.2020.06.008

摘要/Abstract

摘要： 为准确预测我国生产安全事故发展趋势，本文在传统GM(1,1)模型和马尔科夫模型的基础上，结合二者优点提出改进灰色马尔科夫预测模型，并以2005—2018年全国生产安全事故起数为原始序列探讨了改进模型的实际应用。区别于传统灰色残差修正理论，选取灰色模型预测结果的相对误差作为修正指标，2次应用马尔科夫模型对相对误差状态和误差符号状态进行优化预测，并使用平均相对误差和小概率误差对模型进行精度检验。结果表明，改进GM(1,1)-Markov模型预测结果的相对误差为3.0%，较单一灰色预测模型预测误差减少19.5%，预测精度显著提高，同时预测得到2019年我国生产安全事故起数为479。

关键词: 生产安全事故, 预测, GM (1,1)模型, 马尔科夫链

Abstract: In order to accurately predict the trend of the development of production safety accidents in our country, an improved GM(1,1)-Markov prediction model was established based on the traditional GM(1,1) model and the Markov model, and the actual application of this improved model was discussed by using the original sequence about the numbers of production safety accidents from 2005 to 2018. This study differs from traditional grey residual correction theory, and it selected the relative error of the gray prediction result as the correction index, and applied the Markov model to optimized the prediction of the relative error state and the error symbol state respectively, and the accuracy of this model was evaluated by the average relative error and probability of small error. The results showed that the improved GM(1,1)-Markov model had a relative error of 3.0%, and compared with a single gray prediction model, the prediction error was reduced by 19.5%, which prediction accuracy was significantly improved, and the numbers of production safety accidents in China will reach 479 in 2019.

Key words: production safety accidents, prediction, GM(1,1), Markov chain

中图分类号:

王铁骊, 彭恒明. 基于改进GM(1,1)-Markov模型的国内生产安全事故预测研究[J]. 工业工程, 2020, 23(6): 60-67.

WANG Tieli, PENG Hengming. A Study on Prediction of Domestic Production Safety Accidents Based on Improved GM(1,1)-Markov Model[J]. Industrial Engineering Journal, 2020, 23(6): 60-67.

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