A quantum-inspired evolutionary algorithm for fuzzy classification
Waldir Nunes, Marley M. B. R. Vellasco, Ricardo Tanscheit · 2013
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.