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

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http://hdl.handle.net/2183/19747Collections
- Investigación (FIC) [1618]
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Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection Within Fruit Juice ClassificationAuthor(s)
Date
2013-10-21Citation
Fernández-Lozano C, Canto C, Gestal M, et al. Hybrid model based on genetic algorithms and SVM applied to variable selection within fruit juice classification. Sci World J. 2013;2013
Abstract
[Abstract] 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.
Keywords
Algorithms
Beverages
Fruit
Malus
Neural networks (Computer)
Support vector machines
Beverages
Fruit
Malus
Neural networks (Computer)
Support vector machines
Description
Research article
Editor version
Rights
Atribución 3.0 España
ISSN
1537-744X
2356-6140
2356-6140