• 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