DocumentCode :
2491876
Title :
A method of the knowledge acquisition using rough set knowledge reduction algorithm based on PSO
Author :
Xu, Lin ; Dong, Wei ; Wang, Jianhui ; Gu, Shusheng
Author_Institution :
Key Lab. of Process. Ind. Autom., Minist. of Educ. Northeastern Univ., Shenyang
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
5321
Lastpage :
5326
Abstract :
An variable precision rough set (RS) knowledge acquisition based on discrete particle swarm optimization (DPSO-VPRS) are proposed to solve rough set is lack of the ability of anti-jamming, which is used the information entropy is considered as a suitable function in discrete particle swarm algorithm and the attribute dependent degree of variable precision rough set is optimized, and make the classification rules more reliable in the case of noisy data. The study of knowledge acquisition method based on DPSO-VPRS algorithm which is applied into the grate-kiln system in order to acquire knowledge. The mass production process data is deeply analyzed, and find the key factor which determined the finished pellets quality, then attain manufacturing rule of production process control. The results showed that the grate-kiln expert method is effective and has great value as a reference to the palletizing production process control.
Keywords :
entropy; kilns; knowledge acquisition; particle swarm optimisation; process control; production control; rough set theory; PSO; discrete particle swarm optimization; grate-kiln system; information entropy; production process control; rough set knowledge reduction algorithm; variable precision rough set knowledge acquisition; Automation; Control engineering education; Industrial control; Intelligent control; Knowledge acquisition; Laboratories; Mass production; Optimization methods; Particle swarm optimization; Process control; data mining; knowledge reduction; particle swarm optimization; variable precision rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593796
Filename :
4593796
Link To Document :
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