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Categoria WoS
  • Multidisciplinary Sciences - Q2 - T1 - 16/55
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
Pubmed ID: 24453933


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 :.  Sistemas Adaptativos y Bioinspirados en Inteligencia Artificial