Abstract
The risk assessment of gas explosion is difficult to determine due to multiple factors. To solve this problem, a random forest model is applied to the risk assessment of gas explosion disasters in coal mines. Based on the disaster system theory, the pregnant environment, disaster factors and disaster-receiving bodies were used as secondary indicators, and the corresponding 24 tertiary indicators were selected as the evaluation indicator system. The example analysis shows that the accuracy rate of gas explosion risk category prediction of the random forest model is very high (up to 100%), and it is highly practical for small sample problems with high data dimensions; Coal seam spontaneous ignition period led to an average reduction of accuracy of 0.2 and caused the Gini index to drop by an average of 1.5. The average accuracy decrease caused by the qualified rate of air volume at the wind-use site and the coal seam gas content is almost 0, and the decrease of the average Gini index is less than 0.15.
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