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基于IGA-FL融合算法的有色金属选矿精矿品位优化研究
- 张健仁|周新宇|廖辉宝|刘欣宇
- 作者单位：
- 江西省地质调查勘查院基础地质调查所&江西有色地质矿产勘查开发院|江西省地质调查勘查院基础地质调查所&江西有色地质矿产勘查开发院|江西省地质调查勘查院基础地质调查所&江西有色地质矿产勘查开发院|江西省地质调查勘查院基础地质调查所&江西有色地质矿产勘查开发院
基金项目：
- isnull
详细信息：
- 作者简介：
- 张健仁（1987—），男，高级工程师，从事资源勘查工作；E-mail：x123yoyo@163.com
- 通讯作者：
- isnull
- PDF下载
Optimization of concentrate grade in non-ferrous metals mineral processing based on IGA-FL fusion algorithm
- English Author：
- Basic Geological Survey Institute of Jiangxi Geological Survey and Exploration Institute&Jiangxi Nonferrous Geological Exploration and Development Institute|Basic Geological Survey Institute of Jiangxi Geological Survey and Exploration Institute&Jiangxi Nonferrous Geological Exploration and Development Institute|Basic Geological Survey Institute of Jiangxi Geological Survey and Exploration Institute&Jiangxi Nonferrous Geological Exploration and Development Institute|Basic Geological Survey Institute of Jiangxi Geological Survey and Exploration Institute&Jiangxi Nonferrous Geological Exploration and Development Institute
- Unit：
- 摘要
- 在线预览
- 参考文献
摘要:
为优化有色金属选矿过程的精矿品位，将模糊逻辑算法与免疫遗传算法进行融合，设计出了一种IGA-FL融合算法，并基于该融合算法构建有色金属选矿检测模型，对有色金属选矿的精矿品位进行检测和优化。对比试验结果显示，IGA-FL融合算法的数据查全率为99.7 %，计算速度为16.7 bps；基于该算法的检测模型平均检测准确率为97.3 %，检测耗时1.8 s。应用基于IGA-FL融合算法的检测模型后，有色金属选矿精矿品位达到70.5 %，说明该检测模型能够对有色金属选矿的精矿品位进行优化。
关键词:
有色金属选矿；精矿品位；模糊逻辑算法；免疫遗传算法；融合算法；检测模型
Abstract:
To optimize the concentrate grade in the beneficiation process of non-ferrous metals,a fusion algorithm combining fuzzy logic(FL) and immune genetic algorithm(IGA) was developed.Based on this fusion algorithm,a detection model for the beneficiation of non-ferrous metals was constructed to detect and optimize the concentrate grade.Comparative test results show that the data recall rate of the IGA-FL fusion algorithm is 99.7 %,with a computation speed of 16.7 bps.The average detection accuracy of the model based on this algorithm is 97.3 %,with a detection time of 1.8 s.After applying the detection model based on the IGA-FL fusion algorithm,the concentrate grade of non-ferrous metal beneficiation reached 70.5 %,indicating that this model can optimize the concentrate grade effectively.
Keywords:
non-ferrous metal beneficiation;concentrate grade;fuzzy logic algorithm;immune genetic algorithm;fusion algorithm;detection model
