The Technique of Gas Disaster Information Feature Extraction based on Rough Set Theory

Gas accident has become the main contradiction which constrains the safety production of coal mine. It is one of the import issues in the field of coal mine safety to identify and analyze the dangerous factors that lead gas accidents, and establish an effective early-warming support system of gas in coal mine at present. In view of the characteristics of coal mine gas disaster, a high efficient gas disaster feature extraction algorithm based on rough set is proposed, which includes two phases: The algorithm refine the gas disaster information matrix using dimensionality reduction, then uses the entropy and maximum entropy to establish data mining model of gas disaster prediction. The effectiveness and practicality of rough set theory in the prediction of gas disaster and feature extraction was confirmed through practical application.