| A New Tool for CME Arrival Time Prediction using Machine Learning Algorithms: CAT-PUMA | |
| Liu, Jiajia; Ye, Yudong; Shen, Chenglong; Wang, Yuming; Erdelyi, Robert | |
| Department | 空间科学部 |
| Source Publication | ASTROPHYSICAL JOURNAL
 |
| 2018 | |
| Volume | 855Issue:2Pages:109 |
| ISSN | 0004-637X |
| Language | 英语 |
| Keyword | Solar-terrestrial Relations Sun: Coronal Mass Ejections (Cmes) |
| Abstract | Coronal mass ejections (CMEs) are arguably the most violent eruptions in the solar system. CMEs can cause severe disturbances in interplanetary space and can even affect human activities in many aspects, causing damage to infrastructure and loss of revenue. Fast and accurate prediction of CME arrival time is vital to minimize the disruption that CMEs may cause when interacting with geospace. In this paper, we propose a new approach for partial-/full halo CME Arrival Time Prediction Using Machine learning Algorithms (CAT-PUMA). Via detailed analysis of the CME features and solar-wind parameters, we build a prediction engine taking advantage of 182 previously observed geo-effective partial-/full halo CMEs and using algorithms of the Support Vector Machine. We demonstrate that CAT-PUMA is accurate and fast. In particular, predictions made after applying CAT-PUMA to a test set unknown to the engine show a mean absolute prediction error of similar to 5.9 hr within the CME arrival time, with 54% of the predictions having absolute errors less than 5.9 hr. Comparisons with other models reveal that CAT-PUMA has a more accurate prediction for 77% of the events investigated that can be carried out very quickly, i.e., within minutes of providing the necessary input parameters of a CME. A practical guide containing the CAT-PUMA engine and the source code of two examples are available in the Appendix, allowing the community to perform their own applications for prediction using CAT-PUMA. |
| Indexed By | SCI |
| Document Type | 期刊论文 |
| Identifier | http://ir.nssc.ac.cn/handle/122/6239 |
| Collection | 空间科学部 |
| Corresponding Author | Liu, Jiajia; Ye, Yudong; Shen, Chenglong; Wang, Yuming; Erdelyi, Robert |
| Recommended Citation GB/T 7714 | Liu, Jiajia,Ye, Yudong,Shen, Chenglong,et al. A New Tool for CME Arrival Time Prediction using Machine Learning Algorithms: CAT-PUMA[J]. ASTROPHYSICAL JOURNAL,2018,855(2):109. |
| APA | Liu, Jiajia,Ye, Yudong,Shen, Chenglong,Wang, Yuming,&Erdelyi, Robert.(2018).A New Tool for CME Arrival Time Prediction using Machine Learning Algorithms: CAT-PUMA.ASTROPHYSICAL JOURNAL,855(2),109. |
| MLA | Liu, Jiajia,et al."A New Tool for CME Arrival Time Prediction using Machine Learning Algorithms: CAT-PUMA".ASTROPHYSICAL JOURNAL 855.2(2018):109. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 20188552109.pdf（983KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | Application Full Text | |
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