Wavelength Selection for NIR Spectroscopy Based on the Binary Dragonfly Algorithm

Wavelength selection is an important preprocessing issue in near-infrared (NIR) spectroscopy analysis and modeling. Swarm optimization algorithms (such as genetic algorithm, bat algorithm, etc.) have been successfully applied to select the most effective wavelengths in previous studies. However, the...

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Veröffentlicht in:	Molecules (Basel, Switzerland) Jg. 24; H. 3; S. 421
Hauptverfasser:	Chen, Yuanyuan, Wang, Zhibin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 24.01.2019 MDPI
Schlagworte:	binary dragonfly algorithm ensemble learning Exploitation Feature selection Genetic algorithms Methods NIR spectroscopy Optimization Population Quantitative analysis quantitative analysis modeling Random variables Sparsity Spectrum analysis wavelength selection ensemble learning quantitative analysis modeling wavelength selection binary dragonfly algorithm NIR spectroscopy
ISSN:	1420-3049, 1420-3049
Online-Zugang:	Volltext
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