Complete expression trees for evolving fuzzy classifier systems with genetic algorithms and application to network intrusion detection
Abstract
We propose a linear representation scheme for evolving fuzzy rules using the concept of complete binary tree structures. We also use special genetic operators such as gene addition, gene deletion, and variable length crossover. Results show that using these special operators along with the common mutation operator produce useful and minimal structure modifications to the fuzzy expression tree represented by the chromosome. The proposed method (representation and operators) is tested with a number of benchmark data sets including the KDDCup'99 Network Intrusion Detection data.
Publication Title
Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS
Recommended Citation
Gómez, J., Dasgupta, D., Nasraoui, O., & Gonzalez, F. (2002). Complete expression trees for evolving fuzzy classifier systems with genetic algorithms and application to network intrusion detection. Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, 2002-January, 469-474. https://doi.org/10.1109/NAFIPS.2002.1018105
