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Induction of fuzzy classification systems using evolutionary ACO-Based algorithms

Abadeh, M. S ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. DOI: 10.1109/AMS.2007.53
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2007
  4. Abstract:
  5. In this paper we have proposed an evolutionary algorithm to induct fuzzy classification rules. The algorithm uses an ant colony optimization based local searcher to improve the quality of final fuzzy classification system. The proposed algorithm is performed on Intrusion Detection as a high-dimensional classification problem. Results show that the implemented evolutionary ACO-Based algorithm is capable of producing a reliable fuzzy rule based classifier for intrusion detection. © 2007 IEEE
  6. Keywords:
  7. Ant colony optimization ; Artificial intelligence ; Evolutionary algorithms ; Fuzzy inference ; Fuzzy systems ; Intrusion detection ; Mercury (metal) ; Optimization ; Aco-based algorithms ; Fuzzy classification rule ; Fuzzy classification systems ; Fuzzy rule-based classifier ; High-dimensional ; Local searcher ; Algorithms
  8. Source: 1st Asia International Conference on Modelling and Simulation - Asia Modelling Symposium 2007, AMS 2007, 27 March 2007 through 30 March 2007 ; 2007 , Pages 346-351 ; 0769528457 (ISBN); 9780769528458 (ISBN)
  9. URL: https://ieeexplore.ieee.org/abstract/document/4148684