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Induction of Fuzzy Classification Systems Using Evolutionary ACO-Based Algorithms
Prince of Songkla University, Phuket, Thailand March 27-March 30
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AMS.2007.53First Asia International Conference o ...
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Mohammad Saniee Abadeh, Sharif University of Technology, Iran
Jafar Habibi, Sharif University of Technology, Iran
Emad Soroush, University of Victoria, British Columbia, Canada
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.
Citation:
Mohammad Saniee Abadeh, Jafar Habibi, Emad Soroush, "Induction of Fuzzy Classification Systems Using Evolutionary ACO-Based Algorithms," ams, pp.346-351, First Asia International Conference on Modelling & Simulation (AMS'07), 2007
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