Variable selection for multivariate calibration using a genetic algorithm: prediction of additive concentrations in polymer films from Fourier transform-infrared spectral data-Reference-Cited by-同舟云学术

Variable selection for multivariate calibration using a genetic algorithm: prediction of additive concentrations in polymer films from Fourier transform-infrared spectral data

Published:2002-06 Issue:2 Volume:461 Page:189-200
ISSN:0003-2670
Container-title:Analytica Chimica Acta
language:en
Short-container-title:Analytica Chimica Acta

Author:

Leardi Riccardo,Seasholtz Mary Beth,Pell Randy J.

Publisher

Elsevier BV

Subject

Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry

Reference18 articles.

1. Comparison of multivariate calibration methods for quantitative spectral analysis

2. A Primer on Multivariate Calibration

3. Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry

4. Genetic Algorithm-Based Wavelength Selection for the Near-Infrared Determination of Glucose in Biological Matrixes: Initialization Strategies and Effects of Spectral Resolution

5. Comparison of multivariate methods based on latent vectors and methods based on wavelength selection for the analysis of near-infrared spectroscopic data

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