DocumentCode
495092
Title
A Novel Man-Machine Cooperative Intelligent Reduction Algorithm
Author
Yuan, Junpeng ; Su, Cheng ; Su, Jie
Author_Institution
Inst. of Sci. & Tech. of Inf. of China, Beijing, China
Volume
2
fYear
2009
fDate
21-22 May 2009
Firstpage
281
Lastpage
284
Abstract
Although the rough set theory can be deal with uncertain and incomplete knowledge with knowledge reasoning, but for complex systems and some new technology fields, simply rely on the machines learning, the results is not reliable. Absorb the expert knowledge, will help us to grasp the development of this field more accurately. This paper divided expert knowledge into two categories: the decisive expert knowledge and the expertspsila knowledge for reference, then proposed a novel man-machine cooperative intelligent reduction algorithm (RAEK) to search the minimum reduction based on the different status of expert knowledge. Finally, the empirical analysis result on the micro-electromechanical systems (MEMS) field shows that the RAEK algorithm is feasible and efficient.
Keywords
learning (artificial intelligence); man-machine systems; rough set theory; decisive expert knowledge; knowledge reasoning; machines learning; man-machine cooperative intelligent reduction algorithm; microelectromechanical systems; rough set theory; Conference management; Data mining; Engineering management; Financial management; Knowledge management; Man machine systems; Reliability engineering; Set theory; Technology management; Text mining; man-machine cooperative; reduct; rough set theory; text mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Computing Science, 2009. ICIC '09. Second International Conference on
Conference_Location
Manchester
Print_ISBN
978-0-7695-3634-7
Type
conf
DOI
10.1109/ICIC.2009.182
Filename
5169066
Link To Document