Chemometrics: From classical to genetic algorithms

Authors

  • Riccardo Leardi Department of Pharmaceutical and Food Chemistry and Technology, University of Genova

DOI:

https://doi.org/10.3989/gya.2002.v53.i1.294

Keywords:

Calibration, Chemometrics, Classification, Data display, Modeling, Multivariate analysis

Abstract


In this paper the fundamentals of Chemometrics are presented, by means of a quick overview of the most relevant techniques for data display, classification, modeling and calibration. Two emerging techniques such as Genetic Algorithms and Artificial Neural Networks will also be presented. Goal of the paper is to make people aware of the great superiority of multivariate analysis over the commonly used univariate approach. Mathematical and algorithmical details are not presented, since the paper is mainly focused on the general problems to which Chemometrics can be successfully applied in the field of Food Chemistry.

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Published

2002-03-30

How to Cite

1.
Leardi R. Chemometrics: From classical to genetic algorithms. grasasaceites [Internet]. 2002Mar.30 [cited 2022Dec.7];53(1):115-27. Available from: https://grasasyaceites.revistas.csic.es/index.php/grasasyaceites/article/view/294

Issue

Section

Monography