• DocumentCode
    2762169
  • Title

    Hierarchical fuzzy rule-based classification system by evolutionary boosting algorithm

  • Author

    Amouzadi, Azam ; Mirzaei, Abdolreza

  • Author_Institution
    Electr. & Comput. Eng. Dept., Isfahan Univ. of Technol., Isfahan, Iran
  • fYear
    2010
  • fDate
    4-6 Dec. 2010
  • Firstpage
    909
  • Lastpage
    913
  • Abstract
    In this paper, a new Hierarchical fuzzy classifier based on evolutionary boosting algorithms is proposed. The main goal of this paper is to improve the performance of fuzzy rule based classifiers through utilizing hierarchical structure for achieving fuzzy rules. The advantages of hierarchical fuzzy rules generated by evolutionary boosting algorithms are evaluated by comparison between the performance of proposed algorithm and other classifications methods on a set of standard classification tasks.
  • Keywords
    evolutionary computation; fuzzy set theory; knowledge based systems; pattern classification; evolutionary boosting algorithms; fuzzy rule based classification system; hierarchical fuzzy classifier; Accuracy; Algorithm design and analysis; Boosting; Classification algorithms; Gallium; Iris; Training; boosting algorithm; classification; evolutionary algorithm; hierarchical fuzzy rule;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications (IST), 2010 5th International Symposium on
  • Conference_Location
    Tehran
  • Print_ISBN
    978-1-4244-8183-5
  • Type

    conf

  • DOI
    10.1109/ISTEL.2010.5734152
  • Filename
    5734152