Rock burst laws in deep mines based on combined model of membership function and dominance-based rough set
来源期刊：中南大学学报(英文版)2015年第9期
论文作者：LIU Lang CHEN Zhong-qiang WANG Li-guan
文章页码：3591 - 3597
Key words：deep mine; rock burst; membership function; dominance relation; rough set
Abstract: Rock bursts are spontaneous, violent fracture of rock that can occur in deep mines, and the likelihood of rock bursts occurring increases as depth of the mine increases. Rock bursts are also affected by the compressive strength, tensile strength, tangential strength, elastic energy index, etc. of rock, and the relationship between these factors and rock bursts in deep mines is difficult to analyze from quantitative point. Typical rock burst instances as a sample set were collected, and membership function was introduced to process the discrete values of these factors with the discrete factors as condition attributes and rock burst situations as decision attributes. Dominance-based rough set theory was used to generate preference rules of rock burst, and eventually rock burst laws analysis in deep mines with preference relation was taken. The results show that this model for rock burst laws analysis in deep mines is more reasonable and feasible, and the prediction results are more scientific.
LIU Lang(刘浪)1, CHEN Zhong-qiang(陈忠强)2, WANG Li-guan(王李管)3
(1. Energy School, Xi’an University of Science and Technology, Xi’an 710054, China;
2. Beijing General Research Institute of Mining and Metallurgy, Beijing 100070, China;
3. School of Resources and Safety Engineering, Central South University, Changsha 410083, China)
Abstract:Rock bursts are spontaneous, violent fracture of rock that can occur in deep mines, and the likelihood of rock bursts occurring increases as depth of the mine increases. Rock bursts are also affected by the compressive strength, tensile strength, tangential strength, elastic energy index, etc. of rock, and the relationship between these factors and rock bursts in deep mines is difficult to analyze from quantitative point. Typical rock burst instances as a sample set were collected, and membership function was introduced to process the discrete values of these factors with the discrete factors as condition attributes and rock burst situations as decision attributes. Dominance-based rough set theory was used to generate preference rules of rock burst, and eventually rock burst laws analysis in deep mines with preference relation was taken. The results show that this model for rock burst laws analysis in deep mines is more reasonable and feasible, and the prediction results are more scientific.
Key words:deep mine; rock burst; membership function; dominance relation; rough set
