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Mathematical modeling of refractive index based on machine learning (kNN-QSPR) method

Rifkat DavronovAcademy of Sciences, Institute of Mathematics, Tashkent, UzbekistanBakhtiyor RasulevNorth Dakota State University, Fargo, North Dakota, USAFatima AdilovaAcademy of Sciences, Institute of Mathematics, Tashkent, Uzbekistan

2020en

Ochiq kirish: yoʻq

ABI

Annotatsiya

In the present work, we created new software in R system, strictly following to the kNN-QSPR approach, used PaDEL and Dragon Descriptor software for generation of initial set of descriptors and developed the program for automatic scaling. Based on this new software, we propose models of quantitative relationships between refractive indices (RI) and polymer structure. An important conclusion of this study is confirmed by the correct interpretation of the constructed models.

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Mavzular

Computational Drug Discovery Methods Analytical Chemistry and Chromatography Free Radicals and Antioxidants

Identifikatorlar

DOI: 10.1109/aict50176.2020.9368648

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