Operational Pattern Optimization for Copper Flash Smelting Process Based on Pattern Decomposition of Fuzzy Neural Networks

Author

Peng, Xiaobo ; Gui, Weihua ; Li, Yonggang ; Hu, Zhikun ; Wang, Lingyun

Author_Institution

Central South Univ., Changsha

fYear

2007

fDate

May 30 2007-June 1 2007

Firstpage

2328

Lastpage

2333

Abstract

Operational pattern describe a set of on line operational parameters which need to be determined on line. This article proposes operational patterns optimization for copper flash smelting process based on pattern decomposition of fuzzy neural networks. Firstly, the optimal samples set is filtered from the historical samples set. Secondly, this article applies pattern decomposition based on fuzzy neural networks. Finally, chaotic genetic algorithm is used to search the optimal operational sub-pattern. This method is applied in copper flash smelting process which is improved. This method can proved instructs for production.

Keywords

copper; fuzzy neural nets; genetic algorithms; production engineering computing; smelting; chaotic genetic algorithm; copper flash smelting; fuzzy neural networks; operational pattern optimization; pattern decomposition; Chaos; Copper; Data mining; Furnaces; Fuzzy logic; Fuzzy neural networks; Genetic algorithms; Pattern recognition; Production; Smelting; chaotic genetic algorithm; copper flash smelting; operation pattern; pattern decomposition; pattern optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation, 2007. ICCA 2007. IEEE International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4244-0817-7

Electronic_ISBN

978-1-4244-0818-4

Type

conf

DOI

10.1109/ICCA.2007.4376777

Filename

4376777