NAOC Open IR
A survey on machine learning based light curve analysis for variable astronomical sources
Yu, Ce1,2; Li, Kun1,2; Zhang, Yanxia3; Xiao, Jian1,2; Cui, Chenzhou2,3; Tao, Yihan3; Tang, Shanjiang1,2; Sun, Chao1,2; Bi, Chongke1,2
2021-07-04
Source PublicationWILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
ISSN1942-4787
Pages25
AbstractThe improvement of observation capabilities has expanded the scale of new data available for time domain astronomy research, and the accumulation of observational data continues to accelerate. However, traditional data analysis methods are difficult to fully tap the potential scientific value of all data. Therefore, in the current and future research on light curve analysis, it is inevitable to use artificial intelligence (AI) technology to assist in data analysis in order to obtain as many candidates as possible with scientific research goals. This survey reviews important developments in light curve analysis over the past years, summarizes the basic concepts in machine learning and their applications in light curve analysis and concludes perspectives and challenges for light curve analysis in the near future. The full exploration of light curves of variable celestial objects relies heavily on new techniques derived from promotion of machine learning and deep learning in the astronomical big data era. This article is categorized under: Technologies > Machine Learning Technologies > Artificial Intelligence
Keyworddeep learning light curve analysis machine learning variable
Funding OrganizationJoint Research Fund in Astronomy ; Joint Research Fund in Astronomy ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Joint Research Fund in Astronomy ; Joint Research Fund in Astronomy ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Joint Research Fund in Astronomy ; Joint Research Fund in Astronomy ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Joint Research Fund in Astronomy ; Joint Research Fund in Astronomy ; National Natural Science Foundation of China ; National Natural Science Foundation of China
DOI10.1002/widm.1425
WOS KeywordAUTOMATED SUPERVISED CLASSIFICATION ; ECLIPSING BINARIES ; NEURAL-NETWORK ; PHOTOMETRIC CLASSIFICATION ; STARS ; ALGORITHM ; TRANSIENTS ; CANDIDATES ; GENERATION ; SUPERNOVAE
Language英语
Funding ProjectJoint Research Fund in Astronomy[U1731125] ; Joint Research Fund in Astronomy[U1731243] ; Joint Research Fund in Astronomy[U1931130] ; National Natural Science Foundation of China[11803022] ; National Natural Science Foundation of China[11803055] ; National Natural Science Foundation of China[11873066]
Funding OrganizationJoint Research Fund in Astronomy ; Joint Research Fund in Astronomy ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Joint Research Fund in Astronomy ; Joint Research Fund in Astronomy ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Joint Research Fund in Astronomy ; Joint Research Fund in Astronomy ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Joint Research Fund in Astronomy ; Joint Research Fund in Astronomy ; National Natural Science Foundation of China ; National Natural Science Foundation of China
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000669338300001
PublisherWILEY PERIODICALS, INC
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Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/76638
Collection中国科学院国家天文台
Corresponding AuthorYu, Ce
Affiliation1.Tianjin Univ, Coll Intelligence & Comp, 135 Yaguan Rd,Haihe Educ Pk, Tianjin 300350, Peoples R China
2.Chinese Acad Sci, Natl Astron Observ, Beijing, Peoples R China
3.NAOC TJU Joint Res Ctr Astroinformat, Tianjin, Peoples R China
Recommended Citation
GB/T 7714
Yu, Ce,Li, Kun,Zhang, Yanxia,et al. A survey on machine learning based light curve analysis for variable astronomical sources[J]. WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY,2021:25.
APA Yu, Ce.,Li, Kun.,Zhang, Yanxia.,Xiao, Jian.,Cui, Chenzhou.,...&Bi, Chongke.(2021).A survey on machine learning based light curve analysis for variable astronomical sources.WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY,25.
MLA Yu, Ce,et al."A survey on machine learning based light curve analysis for variable astronomical sources".WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2021):25.
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