Prediction and Assessment of the Occupational Risks in the Mining Industry Using the Bayess Theorem

The analysis of existing methods for assessing occupational risks is carried out, and the need for searchinga fundamentally new approach to the assessment and prediction of risks in the mining industry is substantiated. Based on the results of the analysis of modern methods and technologies, it is established that the development of the methodology for assessment and prediction of the occupational risks using Bayes's theorem has significant advantages: simplicity and accessibility for the occupational safety specialists, reproducibility considering many factors of working conditions, as well as the possibility of preventive measures prediction and development. The application of Bayes's theorem is promising in determining cause-and-effect relationships and predicting the occupational morbidity of the employees, which is also an advantage of this methodology for managing occupational risks in the mining industry. Bayes's approaches to modeling are characterized by high performance, intuitively clear in the form of a graph. The example is given concerning the application of Bayes's theorem to assess the risk of a fatal incident taking into account the statistics on the mining industry. Also, the simplest types of Bayes’s trust networks were developed reflecting the possibility of establishing cause-and-effect relationships (both for assessment and prediction), and are the basis for further modeling.