Classification of apple beverages using artificial neural networks with previous variable selection

[1]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[2]  Desire L. Massart,et al.  The Interpretation of Analytical Chemical Data by the Use of Cluster Analysis , 1983 .

[3]  D. E. Goldberg,et al.  Simple Genetic Algorithms and the Minimal, Deceptive Problem , 1987 .

[4]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[5]  John M. Deane,et al.  Testing for redundancy in product quality control test criteria: An application to aviation turbine fuel , 1989 .

[6]  M. Forina,et al.  Chemometrics for analytical chemistry , 1992 .

[7]  J.R.M. Smits,et al.  Practical implementation of neural networks for the interpretation of infrared spectra , 1993 .

[8]  M. S. Sánchez,et al.  Efficiency of multi-layered feed-forward neural networks on classification in relation to linear discriminant analysis, quadratic discriminant analysis and regularized discriminant analysis , 1995 .

[9]  Gilles G. Martin,et al.  Detection of Exogenous Sugars or Organic Acids Addition in Pineapple Juices and Concentrates by 13C IRMS Analysis , 1997 .

[10]  F Despagne,et al.  Neural networks in multivariate calibration. , 1998, The Analyst.

[11]  M. Kubista,et al.  Unambiguous characterization of a single test sample by fluorescence spectroscopy and solvent extraction without use of standards , 1998 .

[12]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[13]  P. Stöber,et al.  Quantitation of the undeclared addition of industrially produced sugar syrups to fruit by juices capillary gas chromatography , 1998 .

[14]  Gerard Downey,et al.  Food and food ingredient authentication by mid-infrared spectroscopy and chemometrics , 1998 .

[15]  Feng Chen,et al.  Simultaneous separation and determination of sugars, ascorbic acid and furanic compounds by HPLC—dual detection , 1999 .

[16]  F. Cadet,et al.  Measurement of sugar content by multidimensional analysis and mid-infrared spectroscopy. , 1999, Talanta.

[17]  John H. Kalivas,et al.  Fundamentals of Calibration Transfer through Procrustes Analysis , 1999 .

[18]  Joseph Maria Kumar Irudayaraj,et al.  Determination of Sugars in Aqueous Mixtures Using Mid-infrared Spectroscopy , 2000 .

[19]  C. Barbas,et al.  Development and validation of a capillary electrophoresis method for direct measurement of isocitric, citric, tartaric and malic acids as adulteration markers in orange juice. , 2000, Journal of chromatography. A.

[20]  L. Rodriguez-Saona,et al.  Rapid analysis of sugars in fruit juices by FT-NIR spectroscopy. , 2001, Carbohydrate research.

[21]  R. Leardi Genetic algorithms in chemometrics and chemistry: a review , 2001 .

[22]  Desire L. Massart,et al.  Feature selection in sequential projection pursuit , 2001 .

[23]  Philip K. Hopke,et al.  Variable selection in classification of environmental soil samples for partial least square and neural network models , 2001 .

[24]  A. J. Moores,et al.  Innovative genetic algorithms for chemoinformatics , 2002 .

[25]  Desire L. Massart,et al.  Feature selection in principal component analysis of analytical data , 2002 .

[26]  Mohammad Hossein Fatemi,et al.  Prediction of bioconcentration factor using genetic algorithm and artificial neural network , 2003 .

[27]  M. P. Gómez-Carracedo,et al.  Classification of commercial apple beverages using a minimum set of mid-IR wavenumbers selected by Procrustes rotation. , 2003, The Analyst.