Data-driven Operational-pattern Optimization for Copper Flash Smelting Process

2009 ◽  
Vol 35 (6) ◽  
pp. 717-724 ◽  
Author(s):  
Wei-Hua Gui ◽  
Chun-Hua YANG ◽  
Yong-Gang LI ◽  
Jian-Jun HE ◽  
Lin-Zi YIN
2000 ◽  
Vol 33 (22) ◽  
pp. 431-436
Author(s):  
S-L. Jämsä-Jounela ◽  
E. Vapaavuori ◽  
T. Salmi ◽  
M. Grönbärj ◽  
M. Vermasvuori

2014 ◽  
Vol 1046 ◽  
pp. 43-49
Author(s):  
Yi Yuan Shao ◽  
Fei Shao

A batch of operating parameters which need to be resolved on line are represented by operating modes.Operating mode optimization for copper flash smelting process based on fuzzy neural networks is presented. First of all, the optimal samples set is screened from the historical samples set. Then mode decomposition based on fuzzy neural networks is used, and chaos genetic algorithm is used to rake the optimal operating sub-pattern.This way is used to copper flash smelting process.The simulation result shows that this way can guide production.


2016 ◽  
Vol 46 ◽  
pp. 66-76 ◽  
Author(s):  
Yong-fang Xie ◽  
Jian-hua Liu ◽  
De-gang Xu ◽  
Wei-hua Gui ◽  
Chun-hua Yang

2007 ◽  
Vol 17 (5) ◽  
pp. 1075-1081 ◽  
Author(s):  
Wei-hua GUI ◽  
Ling-yun WANG ◽  
Chun-hua YANG ◽  
Yong-fang XIE ◽  
Xiao-bo PENG

2021 ◽  
Vol 160 ◽  
pp. 106661
Author(s):  
Huibin Zhang ◽  
Yanan Wang ◽  
Yuzheng He ◽  
Shenghang Xu ◽  
Bin Hu ◽  
...  

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