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The Scientific World Journal
Volume 2013 (2013), Article ID 982438, 13 pages
Research Article

Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

1Information and Communications Technologies Department, Faculty of Computer Science, University of A Coruña, Campus Elviña s/n, 15071, A Coruña, Spain
2Analytical Chemistry Department, Faculty of Sciences, University of A Coruña, Campus da Zapateira s/n, 15008, A Coruña, Spain

Received 24 September 2013; Accepted 21 October 2013

Academic Editors: Z. Cui and X. Yang

Copyright © 2013 C. Fernandez-Lozano et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim 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.