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5. Application and comparison of RNN, RBFNN and MNLR approaches on prediction of flotation column perfo

Application and comparison of RNN, RBFNN and MNLR approaches on prediction of flotation column perfo

来源 :矿业科学技术学报：英文版 | 被引量 : 0次 | 上传用户：xueluowushengkk

【摘 要】

：

Evaluation of grade and recovery plays an important role in process control and plant profitability in mineral processing operations, especially flotation. The

【作 者】

：

Nakhaei Fardis Irannajad Mehdi 

【机 构】

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DepartmentofMining&,MetallurgicalEngineering

【出 处】

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矿业科学技术学报：英文版

【发表日期】

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2015年6期

【关键词】

：

RBF神经网络 性能预测 浮选柱 网络应用 LR方法 径向基函数神经网络 多元非线性回归 MN Flotation columnRadial basis fun 

【基金项目】

：

The authors would like to acknowledge the support of the Department of Research and Development of Sarcheshmeh Copper Plants for this research.

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Evaluation of grade and recovery plays an important role in process control and plant profitability in mineral processing operations, especially flotation. The accurate measurement or estimation of these two parameters, based on the secondary variables, i

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