基于LS-SVM的浮选药剂量优化设定
LS-SVM Based Optimal Setting of Reagent Dosage for Flotation
  
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中文摘要:
      针对矿物浮选在线检测X荧光分析仪缺失、人工检测严重滞后的问题,提出基于最小二乘支持向量机(Least Squares Support Vector Machine,LS-SVM)的浮选药剂量优化设定方法。该方法首先利用历史数据建立基于LS-SVM的药剂量优化模型,然后采用该模型实现浮选药剂量的优化设定。工业数据仿真结果表明,所提方法能够实现浮选生产过程的的指标要求。
英文摘要:
X-ray fluorescence analyzer is in deficiency and manual detection results in large time delay in present online detection of mineral flotation. Aiming at these issues, a novel optimal setting of reagent dosage based on least squares support vector machine (LS-SVM) is proposed. Through obtaining a large amount of history process data from flotation running, LS-SVM is used to implement optimal setting of reagent dosage for flotation process. The simulation results based on experiment data prove the effectiveness of the proposed method.
作者单位
张新林 江西省计量测试研究院 
中文关键词:  浮选  过程数据  LS-SVM  药剂量
英文关键词:flotation  process data  LS-SVM  reagent dosage
基金项目:
DOI:10.11823/j.issn.1674-5795.2015.03.05
引用本文:张新林.基于LS-SVM的浮选药剂量优化设定[J].计测技术,2015,35(3):.
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