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| Improving Pulsar Candidate Identification with Grid Group Uniform Sampling | |
Song, Yi-Ning1,2 ; Chen, Mao-Zheng1,3; Liu, Zhi-Yong1,3
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| 2025-05-01 | |
| Source Publication | RESEARCH IN ASTRONOMY AND ASTROPHYSICS
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| ISSN | 1674-4527 |
| Volume | 25Issue:5Pages:055007 |
| Contribution Rank | 1 |
| Abstract | Pulsar candidate identification is an indispensable task in pulsar science. Based on the characteristics of imbalanced and diverse pulsar data sets, and the lack of a unified processing framework, we first used dimensionality reduction and visualization to analyze potential deficiencies caused by the incompleteness of current data set extraction methods. We found that the limited use of non-pulsar data may lead to bias in the result, which may limit the generalization ability. Based on the dimensionality reduction results, we propose a Grid Group Uniform Sampling (GGUS) method. This data preprocessing method improves the performance of Random Forest, Support Vector Machine, Convolutional Neural Network, and ResNet50 models on Lyon's features, diagnostic plots, and period-dispersion measure (period-DM) plots in the HTRU1 data set. The average recall increased by approximately 0.5%, precision by nearly 2%, and F-1 score by around 1.2% for all models and in all data sets. In the period-DM plots testing, the high-performance ResNet50 algorithm achieved over 98% F-1 using random sampling. GGUS demonstrated further improvements in this test, enhancing the average F-1 score, precision, and recall by approximately 0.07%, 0.1%, and 0.03%, respectively. |
| Keyword | (stars:) pulsars: general methods: data analysis methods: statistical |
| DOI | 10.1088/1674-4527/adc85b |
| Indexed By | SCI |
| Language | 英语 |
| WOS Keyword | CLASSIFICATION ; SELECTION |
| Funding Project | National Key Research and Development Program of China[2018YFA0404603] ; Operation, Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments ; Ministry of Finance of China (MOF) |
| WOS Research Area | Astronomy & Astrophysics |
| WOS Subject | Astronomy & Astrophysics |
| WOS ID | WOS:001485160500001 |
| Publisher | IOP Publishing Ltd |
| Funding Organization | National Key Research and Development Program of China ; Operation, Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments ; Ministry of Finance of China (MOF) |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.xao.ac.cn/handle/45760611-7/7740 |
| Collection | 射电天文研究室_微波技术实验室 |
| Corresponding Author | Chen, Mao-Zheng; Liu, Zhi-Yong |
| Affiliation | 1.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Key Lab Radio Astron & Technol, Beijing 100101, Peoples R China |
| First Author Affilication | Xinjiang Astronomical Observatory, Chinese Academy of Sciences |
| Corresponding Author Affilication | Xinjiang Astronomical Observatory, Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Song, Yi-Ning,Chen, Mao-Zheng,Liu, Zhi-Yong. Improving Pulsar Candidate Identification with Grid Group Uniform Sampling[J]. RESEARCH IN ASTRONOMY AND ASTROPHYSICS,2025,25(5):055007. |
| APA | Song, Yi-Ning,Chen, Mao-Zheng,&Liu, Zhi-Yong.(2025).Improving Pulsar Candidate Identification with Grid Group Uniform Sampling.RESEARCH IN ASTRONOMY AND ASTROPHYSICS,25(5),055007. |
| MLA | Song, Yi-Ning,et al."Improving Pulsar Candidate Identification with Grid Group Uniform Sampling".RESEARCH IN ASTRONOMY AND ASTROPHYSICS 25.5(2025):055007. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Song-2025-Improving （9205KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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