Variable Selection for Partial Least Squares Modeling by Genetic Algorithms
Chu Xiaoli, Yuan Hongfu, Wang Yanbin, Lu Wanzhen (Research Institute of Petroleum Processing, Beijing 100083)
Genetic algorithms (GA), a global searching method, is applied to select wavelength variables of near infrared spectroscpy (NIR) for multivariate calibration made by partial least squares (PLS) method. Two application examples of NIR analysis show that this wavelength selection method for PLS modeling not only simplifies and optimizes calibration model but also increases the prediction ability of calibration model. The method is especially adequate for the system where only PLS is difficult to correlate.
【CateGory Index】： O651