科研之友
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摘要
Cut-off grade and grade of crude ore is crucial to the economic benefit of enterprise and sustainable utilization of resource in mining system. Generally, they are determined by experiment data or worker's experience, and they can't be widely used. In this work, we use genetic algorithm and neural networks nesting method to Simulate the highly complexity and non-linear relationship of mine system, to optimize the cut-off grade and grade of crude ore. The inner layer of nesting is neural networks, which is used to compute loss rate, amount of tailing ore and total cost; the outer layer is genetic algorithm, with cut-off grade and grade of crude ore as chromosome. which is used to get the revenue. These two layers carry out the optimization of cut-off grade and grade of crude ore jointly. Take Daye Iron Mine as a case. the result shows that: During the period of August to November in the year 2007, the optimal cut-off grade is 15.8%, and optimal grade of crude ore is 43.7762-44.1387%. Comparing with the present scheme (cut-off grade is 18%. grade of crude ore is 41-43%). the optimized scheme can improve the present value by 9.01-9.44 million Yuan.
- 出版日期2008
- 单位中国地质大学（北京）
