基于机器学习(kNN-QSPR)方法的折射率数学建模

2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Pub Date : 2020-10-07 DOI:10.1109/AICT50176.2020.9368648

Rifkat Davronov, B. Rasulev, F. Adilova

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引用次数: 0

摘要

在本工作中，我们在R系统中创建了新的软件，严格遵循kNN-QSPR方法，使用PaDEL和Dragon Descriptor软件生成初始描述符集，并开发了自动缩放程序。基于该软件，我们提出了折射率(RI)与聚合物结构之间的定量关系模型。对所构建模型的正确解释证实了本研究的一个重要结论。

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

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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2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)

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