Semi-autogenous mill power model development using gene expression programming

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• 作者：Fatemeh Sadat Hoseinian^a ; ^{f_hoseinian@aut.ac.ir} ; Roohollah Shirani Faradonbeh^b ; Aliakbar Abdollahzadeh^c ; ^a ; Bahram Rezai^a ; Saeed Soltani-Mohammadi^c
• 关键词：Semi-autogenous mill ; Mill power ; Prediction ; Gene expression programming ; Non-linear multiple regression
• 刊名：Powder Technology
• 出版年：2017
• 出版时间：15 February 2017
• 年：2017
• 卷：308
• 期：Complete
• 页码：61-69
• 全文大小：1294 K
• 卷排序：308

文摘

A new predictive model based on GEP was developed to predict mill power of SAG mill. The model can be used for circle optimization in the full-scale SAG mill. The mill power is sensitive to mass flowrate and work index variations than other input parameters.