Research on Accident Prediction in Chemical Industry based on Improved Markov Model
Wang, Wei
Yang, Jing
Liu, Zhanbo
Liu, Gang
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How to Cite

Wang W., Yang J., Liu Z., Liu G., 2017, Research on Accident Prediction in Chemical Industry based on Improved Markov Model , Chemical Engineering Transactions, 59, 1165-1170.
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Abstract

The construction and development of chemical industry park can promote the development of local economy and chemical industry, which also brings new security problems. Because most of the enterprises in chemical industry park are chemical enterprises, the park usually has a large number of major hazards, which frequently causes serious accidents. Generally speaking, most accidents occur mainly in the process of production storage and transportation. So it is very important to analyze and forecast the accidents of chemical enterprise. In the paper, an improved grey Markov model is proposed by combining the classical grey theory and the Markov model. First of all, this paper makes a simple discussion on the grey theory and Markov model. Secondly, we make a Markov prediction on residual random sequence on the basis of grey prediction theory, which realizes the complementary advantages of two traditional models. Finally, the improved prediction model is analyzed by an example, and the results show that the improved Markov prediction model has high prediction accuracy.
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