Genetic Programming with 3sigma Rule for Fault Detection

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{conf/icic/ZhouC07,
  author =       "Yongquan Zhou and Dongyong Chen",
  title =        "Genetic Programming with 3sigma Rule for Fault
                 Detection",
  booktitle =    "Proceedings of the Third International Conference on
                 Intelligent Computing, ICIC 2007",
  year =         "2007",
  editor =       "De-Shuang Huang and Laurent Heutte and Marco Loog",
  volume =       "2",
  series =       "Communications in Computer and Information Science",
  pages =        "543--551",
  address =      "Qingdao, China",
  month =        aug # " 21-24",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming,
                 electro-mechanical device, fault detection",
  isbn13 =       "978-3-540-74281-4",
  DOI =          "doi:10.1007/978-3-540-74282-1_61",
  size =         "9 pages",
  abstract =     "In this paper a new method is presented to solve a
                 series of fault detection problems using 3sigma rule in
                 Genetic Programming (GP). Fault detection can be seen
                 as a problem of multi-class classification. GP methods
                 used to solve problems have a great advantage in their
                 power to represent solutions to complex problems and
                 this advantage remains true in the domain of fault
                 detection. Moreover, diagnosis accuracy can be improved
                 by using 3s rule. In the end of this paper, we use this
                 method to solve the fault detection of
                 electro-mechanical device. The results show that the
                 method uses GP with three sigma rule to solve fault
                 detection of electro-mechanical device outperforms the
                 basic GP and ANN method.",
  notes =        "Advanced Intelligent Computing Theories and
                 Applications. With Aspects of Contemporary Intelligent
                 Computing Techniques.

                 2) College of Computer Science and Information
                 Engineering, Guangxi University, Nanning 530004,
                 Guangxi, China Acknowledgment. Thanks to Mengjie
                 Zhang",
  bibdate =      "2008-09-11",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/icic/icic2007-3.html#ZhouC07",
}

Genetic Programming entries for Yongquan Zhou Dongyong Chen

Citations