Title :
Particle swarm optimization algorithm in the quantitative analysis of near infrared spectroscopy
Author :
Ma, Bibo ; Ji, Haiyan
Author_Institution :
Key Lab. of Modern Precision Agric. Syst. Integration Res., China Agric. Univ., Beijing, China
Abstract :
In this paper, particle swarm optimization (PSO) is used to establish the model of quantitative analysis of near infrared spectral for cereal´ protein. In this paper, 42 samples are selected for the study. Among them, 22 samples are used for modeling, and 20 samples are used for forecasting. The results show that the correlation coefficient of Modeling is 0.98, standard residual is 0.289; the correlation coefficient of forecasting is 0.96, standard residual is 0.397. For the method of PSO, whether it is used for modeling or forecasting, the results are very satisfactory. So, this method could be used in quantitative analysis of near infrared spectra.
Keywords :
crops; forecasting theory; infrared spectra; particle swarm optimisation; proteins; spectrochemical analysis; cereal protein; forecasting correlation coefficient; modeling correlation coefficient; near infrared spectral; near infrared spectroscopy; particle swarm optimization; quantitative analysis; standard residual; Forecasting; Particle swarm optimization; Predictive models; Spectroscopy; Standards; Statistical analysis; Near Infrared spectroscopy; Principal component analysis Particle Swarm Optimization Quantitative analysis;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6359171
