scholarly journals Group-theoretical high-order rotational invariants for structural representations: Application to linearized machine learning interatomic potential

2019 ◽  
Vol 99 (21) ◽  
Author(s):  
Atsuto Seko ◽  
Atsushi Togo ◽  
Isao Tanaka
Keyword(s):  
Machine Learning ◽  
Interatomic Potential ◽  
High Order ◽  
Rotational Invariants

Machine learning interatomic potential developed for molecular simulations on thermal properties of β-Ga2O3

2020 ◽  
Vol 153 (14) ◽  
pp. 144501 ◽  
Author(s):  
Yuan-Bin Liu ◽  
Jia-Yue Yang ◽  
Gong-Ming Xin ◽  
Lin-Hua Liu ◽  
Gábor Csányi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Thermal Properties ◽  
Interatomic Potential ◽  
Molecular Simulations

scholarly journals Insights into the primary radiation damage of silicon by a machine learning interatomic potential

2020 ◽  
Vol 8 (10) ◽  
pp. 364-372 ◽  
Author(s):  
A. Hamedani ◽  
J. Byggmästar ◽  
F. Djurabekova ◽  
G. Alahyarizadeh ◽  
R. Ghaderi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Radiation Damage ◽  
Interatomic Potential ◽  
Primary Radiation

scholarly journals Research on FCM and NHL Based High Order Mining Driven by Big Data

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Zhen Peng ◽  
Jie Peng ◽  
Wei Zhao ◽  
Zhenguo Chen
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
High Order ◽  
Target Level ◽  
Mining Algorithm ◽  
Research Track ◽  
Correlation Degree ◽  
Qualitative Knowledge ◽  
The Index System ◽  
Correlation Weights

In order to get the high order evaluation and correlation degree among big data with the characteristics of multidimension and multigranularity, an FCM and NHL based high order mining algorithm driven by big data is proposed, which is a kind of machine learning based on qualitative knowledge. The algorithm is applied in scientific and technical talent forecast. Driven by the big data of scientific research track of scientific and technical talents, the index system is designed and the big data is automatically acquired and processed. Accordingly, the high order evaluations in dimension level and target level can be inferred by the correlation weights mining. And the outstanding young talents in material field in 2014 have been actively recommended to review department for decision-making.

Sign in / Sign up

Export Citation Format

Share Document