Complete expression trees for evolving fuzzy classifier systems with genetic algorithms and application to network intrusion detection

被引：20

作者：

Gómez, J ^{[1
]}

Dasgupta, D ^{[1
]}

Nasraoui, O ^{[1
]}

Gonzalez, F ^{[1
]}

机构：

[1] Univ Memphis, Dept Math Sci, Div Comp Sci, Memphis, TN 38152 USA

来源：

2002 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY PROCEEDINGS | 2002年

关键词：

D O I：

10.1109/NAFIPS.2002.1018105

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a new 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.

引用

页码：469 / 474

页数：6

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