Quantitative analysis of near infrared spectra by wavelet coefficient regression using a genetic algorithm
✍ Scribed by U. Depczynski; K. Jetter; K. Molt; A. Niemöller
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 338 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0169-7439
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✦ Synopsis
In this paper, we present wavelet coefficient regression WCR in combination with a genetic algorithm GA as a method for multicomponent analysis by Near Infrared Spectrometry. The results are compared with other multivariate calibration Ž . Ž . methods like Fourier coefficient regression FCR , principal component regression PCR and absorbance value regression at Ž . selected wavelengths AVR . It is shown that in comparison to conventional methods, WCR is quite unique by the fact that it is self-adaptive. This means that the steps of pretreatment, selection of specific wavelength regions and calibration are performed automatically in one step.