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
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;
Conference_Titel :
Information and Computing Science, 2009. ICIC '09. Second International Conference on
Conference_Location :
Manchester
Print_ISBN :
978-0-7695-3634-7
DOI :
10.1109/ICIC.2009.182