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基于粗糙模糊集理论的采矿方法优化研究 被引量:12

Study on the Optimization of Mining Methods Based on Rough Fuzzy Set Theory
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摘要 针对传统采矿方法选择存在的弊端,将粗糙集理论与模糊集理论结合应用于采矿方法优化选择,提出液压支护长壁法开采缓倾斜薄矿体的新方法。将采矿方法优化评价结果作为决策属性,综合分析开采安全性、经济技术指标、环境友好等因素,选取11种影响因素作为条件属性,构建样本集合,建立了采矿方法优选指标体系、隶属度矩阵和权重系数矩阵,对拟定采矿方法进行定量分析;应用粗糙集理论中知识依赖性和属性重要性评价法,将模糊数学权系数的确定转化为粗糙集中属性重要性评价问题,从约简结果中提取判别规则,给出预测模型权系数计算方法,确定液压支护长壁式崩落法为最佳开采方案。结果表明,应用粗糙模糊集理论选出的采矿方法具有较强的适应性,达到了安全、高效、低消耗采矿的目的,提高了采矿方法优化选择的科学性和客观性,有较高理论与工程应用价值。 Based on the deficiencies in selection of conventional mining methods, a new method of exploring the gentledip thin ore body with the hydraulic pressure support long wall method was put forward, through integrating the rough set theorywith the fuzzy set theory in mining method optimization. With the comprehensive analysis of mining safety, economic, technicalindex and friendly environment factors, 11 kinds of influence factors are taken as condition attributes and the results of miningoptimization and evaluation are as decision attributes to build the mining method optimization evaluation index system, themembership degree matrix and weight coefficient matrix on the quantitative analysis for the proposed mining methods;Theknowledge dependency and attribute importance of theory evaluation method is applied to transform the weight coefficient offuzzy mathematics into rough set attribute importance evaluation. Discriminated rule is extracted from the reduction results topropose the calculation method of weight coefficient and determine the optimal scheme for hydraulic support long wall cavingmethod. The results show that mining method selected by rough fuzzy set theory are adaptable, with features of safety, high effi-ciency and low consumption. It makes the selection of mining method more scientific and objective, and has a higher theoreticaland engineering practical value.
出处 《金属矿山》 CAS 北大核心 2015年第5期48-51,共4页 Metal Mine
基金 河北省自然科学基金项目(编号:E2015209172) 唐山市科技计划项目(编号:12140208A-12)
关键词 粗糙模糊集理论 评价因素体系 最优采矿方法 优化评价 Rough fuzzy set theory, System of appraisal factors, Optimal mining method, Optimization evaluation
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