caa a22 4500 463219252 CHVBK 20180405153207.0 cr unu---uuuuu 170326e20071201xx s 000 0 eng 10.1134/S1061934807120106 doi (NATIONALLICENCE)springer-10.1134/S1061934807120106 Application of artificial neural networks to the nondestructive determination of ciprofloxacin hydrochloride in powder by short-wavelength NIR spectroscopy [Elektronische Daten] [L. Zhao, Y. Guo, Y. Dou, B. Wang, H. Mi, Y. Ren] The present study is aimed at providing a new short-wavelength near-infrared (NIR) spectroscopic method for the nondestructive quantitative analysis of ciprofloxacin hydrochloride in powder via artificial neural networks (ANNs). For this purpose, the NIR spectra of 90 experimental powder samples in the range 700-1100 mm were analyzed. Four different pretreatment methods—first-derivative, second-derivative, standard normal variate (SNV), and multiplicative scatter correction (MSC)—were applied to three sets of the NIR spectra of the powder samples. Among all of the ANN models, the first-derivative model is found to be the best. The results presented here demonstrate that the short-wavelength NIR region is promising for the fast and reliable determination of the major components in pharmaceuticals. The degree of approximation as an evaluation criterion prevents the overfitting phenomenon occurring in ANNs. Pleiades Publishing, Ltd., 2007 Zhao L. College of Chemistry, Jilin University, 130021, Changchun, China aut Guo Y. College of Chemistry, Jilin University, 130021, Changchun, China aut Dou Y. College of Science, Tianjin University of Science and Technology, 300222, Tianjin, China aut Wang B. College of Chemistry, Jilin University, 130021, Changchun, China aut Mi H. Jilin Institute of Traditional Chinese Medicine, 130021, Changchun, China aut Ren Y. College of Chemistry, Jilin University, 130021, Changchun, China aut Journal of Analytical Chemistry Nauka/Interperiodica 62/12(2007-12-01), 1156-1162 1061-9348 62:12<1156 2007 62 10809 https://doi.org/10.1134/S1061934807120106 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1134/S1061934807120106 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhao L. College of Chemistry, Jilin University, 130021, Changchun, China aut NATIONALLICENCE 700 1- Guo Y. College of Chemistry, Jilin University, 130021, Changchun, China aut NATIONALLICENCE 700 1- Dou Y. College of Science, Tianjin University of Science and Technology, 300222, Tianjin, China aut NATIONALLICENCE 700 1- Wang B. College of Chemistry, Jilin University, 130021, Changchun, China aut NATIONALLICENCE 700 1- Mi H. Jilin Institute of Traditional Chinese Medicine, 130021, Changchun, China aut NATIONALLICENCE 700 1- Ren Y. College of Chemistry, Jilin University, 130021, Changchun, China aut NATIONALLICENCE 773 0- Journal of Analytical Chemistry Nauka/Interperiodica 62/12(2007-12-01), 1156-1162 1061-9348 62:12<1156 2007 62 10809 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer