Genetic algorithm-based wavelength selection method for spectral calibration

In this paper, we propose a genetic algorithm‐based wavelength selection (GAWLS) method for visible and near‐infrared (Vis/NIR) spectral calibration. The objective of GAWLS is to construct robust and predictive regression models by selecting informative wavelength regions. To demonstrate the ability of the proposed method, regression models for soil properties and sugar content of apples are constructed by using GAWLS and other variable selection methods. Copyright © 2010 John Wiley & Sons, Ltd. We propose a genetic algorithm‐based wavelength selection method (GAWLS) for visible and near infrared spectral calibration. The objective of GAWLS is to construct robust and predictive regression models by selecting informative wavelength regions. To demonstrate the ability of the proposed method, regression models for soil properties and sugar content of apples are constructed by using GAWLS and other variable selection methods.