Journal article
Genetic Algorithm-Based Method for Selecting Wavelengths and Model Size for Use with Partial Least-Squares Regression: Application to Near-Infrared Spectroscopy
Analytical chemistry (Washington), Vol.68(23), pp.4200-4212
12/01/1996
DOI: 10.1021/ac9607121
PMID: 8946794
Abstract
Genetic algorithms (GAs) are used to implement an automated wavelength selection procedure for use in building multivariate calibration models based on partial least-squares regression. The method also allows the number of latent variables used in constructing the calibration models to be optimized along with the selection of the wavelengths. The data used to test this methodology are derived from the determination of aqueous organic species by near-infrared spectroscopy. The three data sets employed focus on the determination of (1) methyl isobutyl ketone in water over the range of 1-160 ppm, (2) physiological levels of glucose in a phosphate buffer matrix containing bovine serum albumin and triacetin, and (3) glucose in a human serum matrix. These data sets feature analyte signals near the limit of detection and the presence of significant spectral interferences. Studies are performed to characterize the signal and noise characteristics of the spectral data, and optimal configurations for the GA are found for each data set through experimental design techniques. Despite the complexity of the spectral data, the GA procedure is found to perform well, leading to calibration models that significantly outperform those based on full spectrum analyses. In addition, a significant reduction in the number of spectral pointe required to build the models is realized.
Details
- Title: Subtitle
- Genetic Algorithm-Based Method for Selecting Wavelengths and Model Size for Use with Partial Least-Squares Regression: Application to Near-Infrared Spectroscopy
- Creators
- Arjun S Bangalore - Center for Intelligent Chemical Instrumentation, Department of Chemistry, Clippinger Laboratories, Ohio University, Athens, Ohio 45701-2979Ronald E Shaffer - Center for Intelligent Chemical Instrumentation, Department of Chemistry, Clippinger Laboratories, Ohio University, Athens, Ohio 45701-2979Gary W Small - Center for Intelligent Chemical Instrumentation, Department of Chemistry, Clippinger Laboratories, Ohio University, Athens, Ohio 45701-2979Mark A Arnold - Department of Chemistry, University of Iowa, Iowa City, Iowa 52242
- Resource Type
- Journal article
- Publication Details
- Analytical chemistry (Washington), Vol.68(23), pp.4200-4212
- DOI
- 10.1021/ac9607121
- PMID
- 8946794
- ISSN
- 0003-2700
- eISSN
- 1520-6882
- Language
- English
- Date published
- 12/01/1996
- Academic Unit
- Center for Biocatalysis and Bioprocessing; Fraternal Order of Eagles Diabetes Research Center; Chemistry
- Record Identifier
- 9984216668602771
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