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QSRR analysis of capacity factor of nanoparticle compounds
Joint Authors
Noorizadeh, Hadi
Noorizadeh, Mihrab
Mumtaz, Adnan S.
Source
Journal of Saudi Chemical Society
Issue
Vol. 18, Issue 3 (31 Jul. 2014), pp.183-189, 7 p.
Publisher
Publication Date
2014-07-31
Country of Publication
Saudi Arabia
No. of Pages
7
Main Subjects
Topics
Abstract EN
Genetic algorithm and partial least square (GA–PLS) and Levenberg–Marquardt artificial neural network (L–M ANN) techniques were used to investigate the correlation between capacity factor (k0) and descriptors for 40 nanoparticle compounds which obtained by comprehensive two-dimensional gas chromatography (GC · GC) stationary phases consisting of thin films of gold-centered monolayer protected nanoparticles (MPNs) system.
The applied internal (leavegroup- out cross-validation (LGO-CV)) and external (test set) validation methods were used for the predictive power of models.
The results indicate that L–M ANN can be used as an alternative modeling tool for quantitative structure–retention relationship (QSRR) studies.
This is the first research on the QSRR of the nanoparticle compounds using the L–M ANN.-
American Psychological Association (APA)
Noorizadeh, Hadi& Noorizadeh, Mihrab& Mumtaz, Adnan S.. 2014. QSRR analysis of capacity factor of nanoparticle compounds. Journal of Saudi Chemical Society،Vol. 18, no. 3, pp.183-189.
https://search.emarefa.net/detail/BIM-386973
Modern Language Association (MLA)
Noorizadeh, Hadi…[et al.]. QSRR analysis of capacity factor of nanoparticle compounds. Journal of Saudi Chemical Society Vol. 18, no. 3 (Jul. 2014), pp.183-189.
https://search.emarefa.net/detail/BIM-386973
American Medical Association (AMA)
Noorizadeh, Hadi& Noorizadeh, Mihrab& Mumtaz, Adnan S.. QSRR analysis of capacity factor of nanoparticle compounds. Journal of Saudi Chemical Society. 2014. Vol. 18, no. 3, pp.183-189.
https://search.emarefa.net/detail/BIM-386973
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p.189
Record ID
BIM-386973