Machine Learning in Chemical Dynamics

被引：5

作者：

Biswas, Rupayan ^{[1
]}

Rashmi, Richa ^{[1
]}

Lourderaj, Upakarasamy ^{[1
]}

机构：

[1] HBNI, Sch Chem Sci, Natl Inst Sci Educ & Res, Jatni PO Khurdha, Bhubaneswar, Odisha, India

来源：

RESONANCE-JOURNAL OF SCIENCE EDUCATION | 2020年 / 25卷 / 01期

关键词：

Machine learning; neural networks; Gaussian process for regression; potential energy surface;

D O I：

10.1007/s12045-019-0922-1

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Machine learning has been applied to various fields and is envisaged as the technology of the future. We discuss here, the applications of machine learning methods to represent potential energy surfaces - an important aspect of chemical dynamics. We illustrate the process of machine learning using simple examples, and demonstrate how it can be extended to complicated problems.

引用

页码：59 / 75

页数：17

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