id
	16394
Url
	https://chloe.cnr.it/s/BiDiAr/item/16394
Resource template
	Academic Article
Resource class
	bibo:AcademicArticle
Title
	Identifying Ancient Ceramics Using Laser-Induced Breakdown Spectroscopy Combined with a Back Propagation Neural Network
Creator
	He, Jiao
	Liu, Yongbin
	Pan, Congyuan
	Du, Xuewei
Date
	2019
Language
	eng
Abstract
	This study investigated the rapid identification of ceramics via laser-induced breakdown spectroscopy (LIBS) to realize the identification of ancient ceramics from different regions. Ceramics from different regions may have large differences in their elemental composition. Thus, using LIBS technology for ceramic identification is feasible. The spectral intensities of 11 common elements, namely, Si, Al, Fe, Ca, Mg, Ti, Mn, Na, K, Sr, and Ba, in ceramics were selected as classification indices. Principal component analysis (PCA) and kernel principal component analysis (KPCA) combined with the back propagation (BP) neural network were used to identify ceramics. Furthermore, the effects of the PCA and KPCA data processing methods were compared. Finally, this work aimed to select a suitable method for obtaining spectral data on ceramics identified by LIBS through experiments. Results revealed that LIBS technology could aid the routine, rapid, and on-site analysis of archeological objects to rapidly identify or screen various types of objects.
Is Part Of
	Applied Spectroscopy
Doi
	https://doi.org/10.1177/0003702819861576
Issn
	0003-7028
Issue
	10
Pages
	1201-1207
Volume
	73
Homepage
	https://www.zotero.org/groups/5293298/bidiar/items/AMELUAF9item-list

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