The mining industry plays an important role in the economic development of many countries. However, it is also associated with high risks to human life and the environment. One of the most significant dangers in coal mines is the sudden emissions of coal and gas, which can result in accidents and loss of life. In this article, we present the results of our research on a web service to analyze ways and means of forecasting and preventing sudden emissions of coal and gas in coal mines. The web service provides an efficient and reliable tool for mine operators to manage the risks associated with coal and gas emissions and ensure the safety of their employees.
Keywords: mining, machine learning, python, analysis, forecast.
