截止品位与入选品位的遗传-神经优化模型  

An Integrating GA and ANN Model for Optimizing Cut-off Grade and Grade of Crude Ore

作　　者：刘婷[1] 诸克军[1] 贺勇[1] 李玥[1] 

机构地区：[1]中国地质大学

出　　处：《金属矿山》2010年第2期26-29,共4页Metal Mine

基　　金：国家自然科学基金项目(编号:70573101);武钢科研课题(编号:070429)

摘　　要：合理确定截止品位与人选品佗天系到企业的经济效益和资源的可续性利用，有着重要的理论意义与现实意义。采用遗传算法与神经网络嵌套的动态优化模型，以武钢集团大冶铁矿为例，对其截止品位和人选品位进行动态优化。结果表明，当前大冶铁矿截止品位18％，入选品位41％～42％的生产方案有待改进，当截止品位为15．8％，人选品位取值为43．776％～44．139％，2007年1月-2007年11月的总净现值增加901～944万元？The cut-off grade and grade of crude ore are decision-making variables which are directly related to the economic efficiency of enterprises and the utilization of renewable resources. Determining these two variables has a very im- portant theoretical meaning and obvious practical significance. Taking Daye Iron Mine as an example, the dynamie optimized model of the GA and ANN was adopted to optimize the cut-off grade and grade of crude ore. The result showed that during the period of January to November in 2007, when the optimal cut-off grade was changed from 18% to 15.8% , and optimal grade of crude ore was from 41% - 42% to 43. 776% - 44. 139% , the net present value was improved by 9. O1 - 9.44 million Yuan.

关 键 词：截止品位 入选品位 遗传算法 神经网络 

分 类 号：TD80-9[矿业工程—矿山开采] F224.11[经济管理—国民经济]