Title :
Induction of Fuzzy Classification Systems Using Evolutionary ACO-Based Algorithms
Author :
Abadeh, Mohammad Saniee ; Habibi, Jafar ; Soroush, Emad
Author_Institution :
Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran
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
Keywords :
evolutionary computation; fuzzy set theory; optimisation; pattern classification; ant colony optimization; evolutionary ACO-based algorithm; fuzzy classification rules; fuzzy classification systems; intrusion detection; Ant colony optimization; Computer networks; Computer science; Evolutionary computation; Fuzzy sets; Fuzzy systems; Genetic algorithms; Intrusion detection; Knowledge based systems; Reliability engineering;
Conference_Titel :
Modelling & Simulation, 2007. AMS '07. First Asia International Conference on
Conference_Location :
Phuket
Print_ISBN :
0-7695-2845-7
DOI :
10.1109/AMS.2007.53
