Spectroscopy learning: A machine learning method for study diatomic vibrational spectra including dissociation behavior.

Long, Shanshan; Fu, Jia; Jian, Jun; Fan, Zhixiang; Fan, Qunchao; Xie, Feng; Zhang, Yi; Ma, Jie

Long, Shanshan; Fu, Jia; Jian, Jun; Fan, Zhixiang; Fan, Qunchao; Xie, Feng; Zhang, Yi; Ma, Jie.

Afiliación

Long S; College of Science, Xihua University, Chengdu 610039, China.
Fu J; College of Science, Xihua University, Chengdu 610039, China.
Jian J; College of Science, Xihua University, Chengdu 610039, China.
Fan Z; College of Science, Xihua University, Chengdu 610039, China.
Fan Q; College of Science, Xihua University, Chengdu 610039, China.
Xie F; Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advanced Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China.
Zhang Y; College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China.
Ma J; State Key Laboratory of Quantum Optics and Quantum Optics Devices, Laser Spectroscopy Laboratory, College of Physics and Electronics Engineering, Shanxi University, Taiyuan 030006, China.

MethodsX ; 7: 101127, 2020.

Article en En | MEDLINE | ID: mdl-33251122

Palabras clave

Dissociation energy; Machine learning; Spectral prediction

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: MethodsX Año: 2020 Tipo del documento: Article País de afiliación: China

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