Coal Gas Explosion Hazards Warning Decision Support System Based On Data Mining

The coal industry is a special industry as while as a high-risk industries. The coal mine safety management is one of the most important key link in coal mine enterprise management. The coal mine safety management level, not only directly related to life safety of each mine staff, but also related to the economic development of coal mining enterprises. Shanxi Province is rich in coal resources, but in the aspect of coal mine safety management has loopholes. Coal mine accidents occur frequently, and even some major or outsize explosion accident also happen from time to time. Among them, the typical is the gas outburst accidents. Gas explosion due to a variety of factors such as lower predictability, site gathered and happen with sudden and so on characteristics, cause the harm of this kind of accident often are serious. It leads to heavy casualties and great economic losses for coal mine enterprise. Therefore, coal mine enterprises to strengthen their safety production management system to avoid as much as possible the coal mine accident, is the problem that we urgently need to solve.Therefore, how to mine out the effective information for early warning role of the coal mine safety risk from large amounts of data of coal gas dangerous source has become the start point in this paper to solve some relative issues. For the shortcomings of existing safety management system, this paper introduces the data mining technology. Because the data mining technology has the function of mining out a potential rules and knowledge from a great amount of historical data, so studying the early warning system of Shanxi coal mine safety production by using this technology, building an effective warning model used in coal mine gas hazard, has important theoretical significance and practical significance for improving the management level of safety production in coal mine in Shanxi Province. This article from Shanxi coal industry and its safety production management present situation, according to the characteristics of Shanxi coal mine safety accidents, analyzes and summarizes the problems in the process of Shanxi coal mining mainly includes the aspects of inadequate monitoring system, and the information processing means lagging behind, single monitoring information and low degree of information network. With regard to such problems, this paper puts forward policy recommendations through the establishment of the coal gas explosion hazards warning system to perfect the management of coal mine safety. After analyzing the characteristics of the data mining technology and comparing with the traditional analysis method, this paper powerfully explains the application of data mining technology to establish the feasibility and necessity of mine gas warning system.The key part of the full text studies coal mine gas explosion dangerous source warning system which is based on the mining technology. After specific descripting the mechanism and operation steps of coal gas warning system which is based on data mining, this paper focused on the early the process of construction of warning system model, which detailed introduced the main three algorithms when using data mining technology construct model, such as rough intensive reduction algorithm and FCM clustering algorithm and RBF neural network construction. Model building results is to establish the corresponding safety evaluation index system, and to make a reasonable explanation of the evaluation result.After constructing coal mine gas explosion hazards warning system based on data mining technology, this paper put forward through the reasonable design of mine gas hazard warning decision support system to improve the practicality of the former. And analysis instances of guandi mine in Shanxi, on the analysis of the problems in coal mine safety management, Suggestions and design using hazards warning decision support system to solve the problems, also further shows the feasibility and rationality of the system. Innovation of this paper is using the data mining technology as the foundation, to construct coal mine gas explosion hazards warning and decision support system. According to the characteristics of coal mine safety monitoring data, this paper comprehensive uses of rough sets theory and FCM clustering algorithm and RBF neural network this three kinds of data mining algorithm, analyzes and processes the monitoring and provide real-time dynamic information for the early warning dynamic system, so as to improve the efficiency and reliability of the early warning system, play the role of prediction and prevention of coal mine safety accident.