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Research on miners' unsafe behavior based on Bayesian network

In order to scientifically prevent coal mine safety accidents, the Bayesian network (BN) method is used to put forward 26 Bayesian network nodes from five levels: personal factor level, group factor level, management factor level, environmental factor level and equipment and facilities level, and the probability evaluation index system of miners' unsafe behavior is established. In view of the fuzziness of the evaluation of the influencing factors of miners' unsafe behavior, the language evaluation level is used to describe the variables. Through the consistency processing of Delphi method, the conditional probability of Bayesian network nodes is determined, and the sensitivity of the results is analyzed. The results show that among the 26 influencing factors, the sensitivity of work discipline is the largest, that is, the influence of work discipline on miners' unsafe behavior is the largest, followed by group pressure.