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QSRR analysis of capacity factor of nanoparticle compounds
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نویسنده
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noorizadeh h. ,noorizadeh m. ,mumtaz a.s.
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منبع
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journal of saudi chemical society - 2014 - دوره : 18 - شماره : 3 - صفحه:183 -189
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چکیده
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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 (k') 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 (leave-group-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. © 2011.
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کلیدواژه
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Capacity factor; Comprehensive two-dimensional gas chromatography; Gold-centered monolayer protected nanoparticles; Levenberg-Marquardt artificial neural network; Nanoparticle compounds
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آدرس
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department of chemistry,ilam branch,islamic azad university, ایران, young researchers club,ilam branch,islamic azad university, ایران, department of chemistry,taif university, Saudi Arabia
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Authors
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