Induction of Fuzzy Classification Systems Using Evolutionary ACO-Based Algorithms

Authors:
Mohammad Saniee Abadeh;Jafar Habibi;Emad Soroush
Affiliations:
Sharif University of Technology, Iran;Sharif University of Technology, Iran;University of Victoria, British Columbia, Canada
Venue:
AMS '07 Proceedings of the First Asia International Conference on Modelling & Simulation
Year:
2007

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Abstract

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.