Key points are not available for this paper at this time.
In the coal mining process, a large amount of harmful gases will be produced, which we call "gas". The main component of gas is methane. After the methane concentration reaches a certain limit, an explosion will occur, seriously affecting the safety of the production of coal mines. Gas safety situational awareness is an important basis for gas early warning. In order to take appropriate measures for different levels of risk, the safety situation level is classified into five levels, which can be attributed to the classification problem in machine learning. We propose a gas security situation analysis model based on the Schweizer-Sklar rule (GSSAM-SSR) using the multiweighted Schweizer-Sklar triangular norm array combination rule (SSR). First, the raw data are preprocessed. The model uses
Rong Liang (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: