Title :
Nondestructive quantitative analysis of compound paracetamol and diphenhydramine hydrochloride powder using RBF networks
Author :
Zheng, Hong ; Wan, Li-Ming ; Jiang, Jing-Qing ; Liang, Yan-Chun
Author_Institution :
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Abstract :
A method for simultaneous analysis of the two components of compound paracetamol and diphenhydramine hydrochloride powdered drugs on near-infrared (NIR) spectroscopy is developed by using a radial basis function (RBF) network. Nearest neighbor-clustering algorithm is used as the learning algorithm of RBF network. Comparisons of the results obtained from the RBF models with those from BP models show that it is feasible to use the RBF network in nondestructive quantitative analysis of the components of drugs.
Keywords :
chemical analysis; drugs; infrared spectra; learning (artificial intelligence); organic compounds; radial basis function networks; spectroscopy computing; NIR spectroscopy; RBF networks; drug components; learning algorithm; near-infrared spectroscopy; nearest neighbor-clustering; nondestructive quantitative analysis; paracetamol-diphenhydramine hydrochloride powder drugs; radial basis function network; Artificial neural networks; Clustering algorithms; Computer science; Drugs; Educational institutions; Educational technology; Knowledge engineering; Powders; Radial basis function networks; Spectroscopy; Neural network; near-infrared spectroscopy; nondestructive quantitative analysis; radial basis function;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527656
