QSPR modelling of stability constants of metal thiosemicarbazone complexes using multivariate regression methods and artificial neural network

Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/70340

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DC Field	Value	Language
dc.contributor.author	Nguyen, Minh Quang	-
dc.contributor.author	Tran, Nguyen Minh An	-
dc.contributor.author	Nguyen, Hoang Minh	-
dc.contributor.author	Tran, Xuan Mau	-
dc.contributor.author	Pham, Van Tat	-
dc.date.accessioned	2021-12-14T09:02:53Z	-
dc.date.available	2021-12-14T09:02:53Z	-
dc.date.issued	2018	-
dc.identifier.issn	2525-2267	-
dc.identifier.uri	https://dspace.ctu.edu.vn/jspui/handle/123456789/70340	-
dc.description.abstract	In this study the stability constants of metal-thiosemicarbazone complexes, log β11 were determined by using the quantitative structure property relationship (QSPR) models. The molecular descriptors, physicochemical and quantum descriptors of complexes were generated from molecular geometric structure and semi-empirical quantum calculation PM7 and PM7/sparkle.	vi_VN
dc.language.iso	en	vi_VN
dc.relation.ispartofseries	Tạp chí Khoa học và Công nghệ Trường Đại học Công nghiệp Thành pố Hồ Chí Minh;Số 36A - Tr.186-197	-
dc.subject	QSPR	vi_VN
dc.subject	Ordinary least squareregression	vi_VN
dc.subject	Partialleast square	vi_VN
dc.subject	Primary component regression	vi_VN
dc.title	QSPR modelling of stability constants of metal thiosemicarbazone complexes using multivariate regression methods and artificial neural network	vi_VN
dc.type	Article	vi_VN
Appears in Collections:	Khoa học và Công nghệ Trường Đại học Công nghiệp Thành phố Hồ Chí Minh

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