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随着矿石价格的不断变化以及矿山设备的不断更新,为了达到矿山经济效益的最大化,通过智能算法来优化放矿截止品位与入选品位。以程潮铁矿2015年的生产指标作为参数,建立金属回收率、成本与截止品位和入选品位的BP神经网络,确定它们之间的函数关系。通过遗传算法,在模糊理论的基础上以精矿量与利润两个经济指标构建综合隶属度模型,优选出经济合理的截止品位与入选品位组合。结论证明,程潮铁矿的截止品位选取为15.70%,入选品位选取为23.13%时,精矿量提升了8474.77t,利润增加了5709407.58元。
With the continuous changes in the ore price and the continuous updating of mining equipment, in order to achieve the maximization of mine economic benefits, the intelligent algorithm is used to optimize the cut-off grade and the selected grade. Taking the production index of Chengchao Iron Mine in 2015 as a parameter, a BP neural network with metal recovery, cost, cut-off grade and selected grade was established to determine the functional relationship among them. Based on the fuzzy theory and genetic algorithm, the integrated membership degree model is constructed based on the two economic indicators of the quantity and profit of concentrate, and the reasonable combination of the cut-off grade and the selected grade is selected. The conclusion proves that the cut-off grade of Chengchao Iron Mine is 15.70%. When the selected grade is 23.13%, the amount of concentrate increases 8474.77t and the profit increases by 5709407.58 yuan.