Artificial neural network modeling for evaluating the power consumption of silicon production in submerged arc furnaces

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• 作者：Zhengjie Chen^a ; ^b ; ^c ; Wenhui Ma^a ; ^b ; ^c ; ^{mwhsilicon@126.com} ; Kuixian Wei^a ; ^b ; ^c ; Jijun Wu^a ; ^b ; Shaoyuan Li^a ; ^c ; Keqiang Xie^a ; ^b ; Guoqiang Lv^a ; ^b
• 关键词：Power consumption ; Submerged arc furnace ; Silicon ; Pearson correlation coefficient ; Contour diagrams ; Artificial neural networks
• 刊名：Applied Thermal Engineering
• 出版年：2017
• 出版时间：5 February 2017
• 年：2017
• 卷：112
• 期：Complete
• 页码：226-236
• 全文大小：3562 K
• 卷排序：112

文摘

The effect of metal oxide on power consumption was studied. Pearson correlation coefficient between oxide contents and power consumption was investigated. The interactive effects among the main oxide matter and remaining trace oxide matter was studied by the contour diagrams. Artificial neural network modeling was used for evaluating the power consumption of silicon production.