First Asia International Conference on Modelling & Simulation (AMS'07)
Induction of Fuzzy Classification Systems Using Evolutionary ACO-Based Algorithms
Prince of Songkla University, Phuket, Thailand
March 27-March 30
ISBN: 0-7695-2845-7
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