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Titulo:	Hybrid model based on Genetic Algorithms and SVM applied to variable selection within fruit juice classification
Tipo:	revista internacional
Fecha:	12,2013
Revista:	The Scientific World Journal. Issue: Recent Advances on Bioinspired Computation JCR Journal; Impact Factor: 1.219 SCIMago SJR: 0.510 Citas ISI: 1 Citas Scopus: 1 Citas Google Scholar: 2
Volumen:	2013. ID 982438
Paginas:	1-13
ISSN:	1537-744X
Editorial:	Hindawi Publishing Corporation
	EE.UU.
doi:	http://dx.doi.org/10.1155/2013/982438
Pubmed ID:	24453933

Abstract:

Given the background of the use of Neural Networks in problems of apple juice classification, this paper is aimed at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected.

SABIA

.: SABIA :. Sistemas Adaptativos y Bioinspirados en Inteligencia Artificial