基于未确知测度理论和粗糙集的开采方案优选

Mining method optimization of sublevel-caving mine based on uncertainty measurement theory and rough set

以国内某矿山为例,结合矿山已有开采方法,选取采场生产能力、环保费用,采矿方法转换难易程度等9个影响因素作为评价指标,利用未确知测度理论获得待选方案的评价等级并将其作为粗糙集的决策属性,对指标进行属性约简。再利用未知测度理论结合约简后的属性指标进行计算,获得各方案的优越度,确定无底柱分段崩落法和充填法联合开采以及分段凿岩阶段出矿嗣后充填法作为最优方案,符合矿山实际,对其他类似矿山有一定的参考意义。

Taking a domestic mine as example with consideration of the existing mining method, nine factors such as stope capacity, environmental costs, difficulty of mining method conversion as e- valuation indexes are selected Rank alternatives of preliminary plans are obtained with uncertainty measurement theory as deci- sion attributes of the rough set to attribute reduction of indicators and simplify the calculation, The superiority of preliminary plans is obtained by calculating the re-using uncertainty measurement theory with reduction attribute indexes to determine the combina- tion of sublevel caving mining method and the filling method, sub- level drilling and stope mining and subsequent filling method as the optimal solutions, which are consistent with the method tested in the mine. This model can provide a reference for other similar mines.