Servicios Personalizados
Revista
Articulo
Indicadores
Citado por SciELO
Accesos
Links relacionados
Similares en SciELO
Compartir
Archivos Venezolanos de Farmacología y Terapéutica
versión impresa ISSN 0798-0264
Resumen
LEON, Miguel et al. Application of fuzzy logic and genetic algorithms for classification of malignant neoplastic diseases treatments. AVFT [online]. 2016, vol.35, n.2, pp.36-41. ISSN 0798-0264.
A fuzzy classifier is a system that assigns a class label to object based on a description of it and makes use of fuzzy sets as part of its operation. Its functioning can be optimized using genetic algorithms, ensuring viable solutions. The paper proposes a fuzzy classifier optimized using a genetic algorithm hybridized with a fuzzy clustering technique. A prototype is implemented and evaluated with synthetic reference data sets as possible classification problems treatments for malignant neoplastic diseases. The results are compared with other classifiers found in the literature on the same test data. The conclusion is that the proposed method obtained similar results with functions easier to interpret.
Palabras clave : fuzzy logic; genetic algorithms; fuzzy classifier; hybrid genetic algorithm; malignant neoplastic diseases.