CHEN Changhui. Coal mine safety early warning model based on rough set fusion least squares support vector machine[J]. CHINA MINING MAGAZINE, 2020, 29(6): 76-80. DOI: 10.12075/j.issn.1004-4051.2020.06.026
    Citation: CHEN Changhui. Coal mine safety early warning model based on rough set fusion least squares support vector machine[J]. CHINA MINING MAGAZINE, 2020, 29(6): 76-80. DOI: 10.12075/j.issn.1004-4051.2020.06.026

    Coal mine safety early warning model based on rough set fusion least squares support vector machine

    • Aiming at the problems of many factors affecting coal mine safety, the correlation among various factors and the difficulty in collecting sample information, the risk of coal mine safety production system is analyzed.The index system of coal mine safety influence factors is constructed from four aspects.Based on rough set theory and least squares support vector machine (LS-SVM), an early warning model of coal mine safety machine is proposed.The calculation results of the model are trained and tested by taking the measured data.the results of the early warning model are trained and tested.The results show that the least squares support vector machine based on rough set fusion can effectively improve the efficiency of early warning and reflect the influence of various control factors on coal mine safety.The fitting accuracy between the calculated results and sample values is high, which has important and practical significance to ensure the safety production of coal mines.
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