Title :
An approach of CBR to intelligent optional control architecture for rare-earth extraction process based on Rough Set
Author :
Jinhong, Gong ; Hui, Yang
Author_Institution :
Sch. of Electron. & Electr. Eng., East China Jiaotong Univ., Nanchang, China
Abstract :
On the characteristics of complex rare-earth extraction process, difficult system craft operation, achieving hardly automatic control technology, and inaccessibility to on-line component content, the paper lodge a technology for the extraction of rare earth based on the case based reasoning (CBR) technology with rough-set. It can optimize the manual enactment in the rare-earth extraction process in place of the enactment to feeding liquid flowrate, forecast the information of component content. Also it designs structure of the case and establishes the cases library on the base of the dynamical equilibrium model of the extraction separation process and a large amount of historical data, and simplify the knowledge of the cases library and refines the rules with rough set theory, so the cases library is optimized and the speed of retrieval is greatly improved at the same time. The method can achieve the intelligent optimal control for the rare-earth extraction process effectively and obtain good forecast-value of component content. An industrial experiment in the extraction process using this CBR technology with rough set proves its effectiveness and accuracy.
Keywords :
case-based reasoning; metallurgical industries; optimal control; production engineering computing; rare earth metals; rough set theory; automatic control technology; case based reasoning technology; dynamical equilibrium model; extraction separation process; intelligent optimal control; intelligent optional control architecture; rare-earth extraction process; rough set theory; system craft operation; Automatic control; Data mining; Design optimization; Information retrieval; Intelligent control; Libraries; Paper technology; Refining; Separation processes; Set theory; Case Based Reasoning; Optimal Setting; Rare Earth Extract; Rough Set;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5191842