quantitative structure—retention relationship analysis of nanoparticle compounds
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abstract
genetic algorithm and partial least square (ga-pls), the kernel pls (kpls) and levenberg-marquardt artificial neural network (l-m ann) techniques were used to investigate the correlationbetween retention time (rt) and descriptors for 15 nanoparticle compounds which obtained by thecomprehensive two dimensional gas chromatography system (gc x gc). application of thedodecanethiol monolayer-protected gold nanoparticle (mpn) column was for a high-speed separationas the second column of gc x gc. the l-m ann model with the final optimum networkarchitecture of [9-4-1] gave a significantly better performance than the other models. this is the firstresearch on the quantitative structure—retention relationship (qsrr) of the nanoparticle compoundsusing the ga-pls, ga-kpls and l-m ann.
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Journal title:
journal of physical & theoretical chemistryISSN
volume 8
issue 2 2011
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