Sintonización de Clasificadores Difusos Mediante un Algoritmo Memético Adaptativo ( Fuzzy Classifiers Tuning Through an Adaptive Memetic Algorithm)

Cristhian Murcia (cjmurciag@correo.udistrital.edu.co), Gustavo Bonilla (gabonillac@correo.udistrital.edu.co), Miguel Melgarejo (mmelgarejo@ieee.org)


Universidad Distrital Francisco José de Caldas
This paper appears in: Revista IEEE América Latina

Publication Date: March 2014
Volume: 12,   Issue: 2 
ISSN: 1548-0992


Abstract:
This paper presents a methodological approach for tuning the fuzzy rules of a fuzzy classifier using an adaptive memetic algorithm. The approach is validated over two benchmark problems in terms of classification error and computational effort. In addition, it compares the performance of memetic, genetic and adaptive memetic algorithms over the benchmark problems. These results show a favorable trend towards the tuning of the classifiers through the adaptive memetic perspective.

Index Terms:
Memetic Algorithm, Adaptative, Hyiperheuristic, Classifiers, Fuzzy Systems, tuning, local improvement, Breast Cancer, Wine   


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