Selection of variables by genetic algorithms to classify apple beverages by artificial neural networks

Applied Artificial Intelligence

Volumn 19, Issue 2, 2005, Pages 181-198

  Gestal, Marcos ^a   Gómez Carracedo, María Paz ^a   Andrade, Jose Manuel ^a   Dorado, Julián ^a   Fernández, Esther ^a   Prada, Darío ^a   Pazos, Alejandro ^a  

^a UNIVERSITY OF A CORUÑA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

BEVERAGES; GENETIC ALGORITHMS; INFRARED SPECTROSCOPY; LIQUID CHROMATOGRAPHY; NEURAL NETWORKS;

APPLE BEVERAGES; DIGITIZED SPECTRA; HEALTH PROTECTION;

FRUIT JUICES;

EID: 13844272692     PISSN: 08839514     EISSN: None     Source Type: Journal    
DOI: 10.1080/08839510590901921     Document Type: Article

References (17)

1. Bishop, C. M. 1995. Neural Networks for Pattern Recognition. New York: Oxford University Press.
2. Braakman, L. 2002. What to get ready for. Food Engineering and Ingredients. 27(6):14-19.
3. Braakman, L. 2003. Balancing taste and shelf life. Food Engineering and Ingredients. 28(1):45-47.
4. Dorado, J., A. Pazos, M. Gestal, M. P. Gómez-Carracedo, J. M. Andrade, D. Prada, and E. Fernández. 2002. Selección de variables en espectroscopia IR mediante algoritmos genéticos para clasificar zumos de manzana en function de su concentration de azucares. V Reunion Nacional del Grupo de Espectroscopía Analitica. Barcelona, Spain: Sitges.
5. Goldberg, D. E. 1987. Simple genetic algorithms and the minimal deceptive problem. In Genetic Algorithms and Simulated Annealing, ed. L. Davis, 74-88. London: Pitman.
6. Goldberg, D. E. 1989. Genetic Algorithms in search, Optimization and Machine Learning. Reading, MA: Addisson-Wesley.
7. Haykin, S. 1999. Neural Networks: A Comprehensive Foundation, Second Edition. New Jersey: Prentice Hall.
8. Holland, J. F. 1975. Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press.
9. Jamin, E.,J. Gonzalez, G. Remaud, N. Naulet, and G. Martin. 1997. Detection of exogenous sugars or organic acids addition in pineapple juices and concentrates by 13C IRMS analysis. J. of Agric. Food Chem. 45(10):3961-3967.
10. Krzanowski, W. J. 1990. Principles of Multivariate Analysis: A user's Perspective. Oxford: Clarendon Press.
11. Massart, D. L. and L. Kaufman. 1989. The Interpretation of Analytical Chemical Data by the Used of Cluster Analysis. Malabar, Florida: Krieger Publishing (John Wiley and Sons).
12. Massart, D. L., B. G. M. Vandeginste, L. M. C. Buydens, S. De Jong, P. J. Lewi, and J. Smeyers-Verbeke. 1997. Handbook of Chemometrics and Qualimetrics. Amsterdam: Elsevier.
13. Meloun, M., J. Militky, and M. Forina. 1992. Chemometrics for Analytical Chemistry. New York: Ellis Horwood.
14. Saavedra, L., A. García, and C. Barbas. 2000. Development and validation of a capillary electrophoresis method for direct measurement of isocitric, citric, tartaric and malic acids and adulteration markers in orange juice. J. Chromatography A. 881:395-401.
15. Sivakesava, S. and J. Irudayaraj. 2000. Determination of sugars in aqueous mixtures using mid-infrared spectroscopy. Appl. Eng. Agricult. 16:543-550.
16. Stöber, P., G. G. Martin, and T. L. Peppard. 1998. Quantitation of the undeclared addition of industrially produced sugar syrups to fruit juices capillary gas Chromatography. Deutsche Lebensmittel-Rundschau. 94(9):309-316.
17. Yuan, J. P. and F. Chen. 1999. Simultaneous separation and determination of sugars, ascorbic acid and furanic compounds by HPLC-dual detection. Food Chemistry. 64:423-427.