A quantum-inspired evolutionary algorithm for fuzzy classification

被引：0
|
作者：
Nunes, Waldir [1 ]
Vellasco, Marley [1 ]
Tanscheit, Ricardo [1 ]
机构：
[1] Pontifical Catholic Univ Rio de Janeiro PUC Rio, Dept Elect Engn, Rio De Janeiro, RJ, Brazil
来源：
PROCEEDINGS OF THE 2013 JOINT IFSA WORLD CONGRESS AND NAFIPS ANNUAL MEETING (IFSA/NAFIPS) | 2013年
关键词：
Fuzzy systems; Quantum inspired genetic algorithms; Genetic fuzzy systems; SYSTEMS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a new optimization algorithm based on quantum-inspired evolutionary techniques that simultaneously incorporates two important features: (i) the treatment of multiple objectives and (ii) the treatment of related categorical attributes, applicable to a specific form of combinatorial optimization. The proposed optimization algorithm is applied to the development of fuzzy inference systems for classification, seeking to achieve the goals of maximum efficiency ratings and high level of system interpretability.
引用
收藏
页码：29 / 34
页数：6
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