基于统计模糊权重和模糊区间评价的采矿方法优选模型

The optimal selection model of mining method based on statistical fuzzy weights and fuzzy interval evaluation

针对采矿方法优选过程中评价指标及其权重值较难确定的问题,提出了基于统计方法的指标权重值计算方法。通过对大量采矿方法优选学术论文的统计和分析,综合分析了大量采矿行业专家在采矿方法优选过程中评价指标模型,确定了以基于被选次数统计的指标权重值和带权重统计的指标权重值为区间边界、二者综合计算的加权指标权重值为最大可能值的评价指标模糊区间权重值。根据模糊评价原理建立了模糊区间评价模型,建立了一种计算简便的区间数概率密度函数,并设计了一种区间数排序方法,利用模糊区间评价方法对评价方案进行了最大可能值排序和区间数排序,并综合考虑两种排序结果确定了最终排序。采用基于统计模糊权重和模糊区间评价的采矿方法优选模型进行了某多层矿床采矿方法优选,应用案例表明,用模糊区间数表示评价指标权重值更加准确、合理,评价过程较好地模拟了优选过程中的模糊性和不确定性,对采矿方法优选具有一定参考意义。

In order to solve the problem in selecting evaluation indexes and determining their weights, the calculation method of evaluation index weights based on statistical method was proposed. The fuzzy interval weights of evaluation indexes was determined which was combined by the statistical weights based on selected times of index weights and the statistical weights of evaluation indexes with their weights as the boundary of fuzzy interval weights, and the comprehensive calculation of two kinds of statistical weights as the most possible numbers of fuzzy interval weights, after comprehensive analyzing of numerous mining experts＇ evaluation index models by counting and analyzing their papers of mining method optimization. The fuzzy interval evaluation model and a probability density function of interval number which calculated succinctly are established, and a ranking method of interval numbers is also designed based on the fuzzy evaluation principles. Evaluation methods are ranked as the maximum possibility and the interval numbers by using the fuzzy interval evaluation method, the final ranking of evaluation methods was determined by considering the two kinds of ranking methods. The optimal selection of mining method of a multilayer mineral deposit by applying the optimal selection model of mining method based on statistical fuzzy weights and fuzzy interval evaluation shows that it is more accurate and reasonable to represent the value of evaluation index weights by fuzzy interval numbers, and the evaluation process is better to simulate the fuzziness and uncertainty during the optimization, which is valuable for the optimal selection of mining method.