Full-Disk Solar Flare Forecasting Model Based on Data Mining Method
Solar flare is one of the violent solar eruptive phenomena; many solar flare forecasting models are built based on the properties of active regions. However, most of these models only focus on active regions within 30° of solar disk center because of the projection effect. Using cost sensitive decis...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Advances in Astronomy |
| Online Access: | http://dx.doi.org/10.1155/2019/5190353 |
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| _version_ | 1850233248296206336 |
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| author | Rong Li Yong Du |
| author_facet | Rong Li Yong Du |
| author_sort | Rong Li |
| collection | DOAJ |
| description | Solar flare is one of the violent solar eruptive phenomena; many solar flare forecasting models are built based on the properties of active regions. However, most of these models only focus on active regions within 30° of solar disk center because of the projection effect. Using cost sensitive decision tree algorithm, we build two solar flare forecasting models from the active regions within 30° of solar disk center and outside 30° of solar disk center, respectively. The performances of these two models are compared and analyzed. Merging these two models into a single one, we obtain a full-disk solar flare forecasting model. |
| format | Article |
| id | doaj-art-051edf2fcab744b79a6832310042b1c1 |
| institution | OA Journals |
| issn | 1687-7969 1687-7977 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Astronomy |
| spelling | doaj-art-051edf2fcab744b79a6832310042b1c12025-08-20T02:02:58ZengWileyAdvances in Astronomy1687-79691687-79772019-01-01201910.1155/2019/51903535190353Full-Disk Solar Flare Forecasting Model Based on Data Mining MethodRong Li0Yong Du1School of Information, Beijing Wuzi University, Beijing 101149, ChinaDepartment of Electrical and Information Engineering, Northeast Agricultural University, Harbin, ChinaSolar flare is one of the violent solar eruptive phenomena; many solar flare forecasting models are built based on the properties of active regions. However, most of these models only focus on active regions within 30° of solar disk center because of the projection effect. Using cost sensitive decision tree algorithm, we build two solar flare forecasting models from the active regions within 30° of solar disk center and outside 30° of solar disk center, respectively. The performances of these two models are compared and analyzed. Merging these two models into a single one, we obtain a full-disk solar flare forecasting model.http://dx.doi.org/10.1155/2019/5190353 |
| spellingShingle | Rong Li Yong Du Full-Disk Solar Flare Forecasting Model Based on Data Mining Method Advances in Astronomy |
| title | Full-Disk Solar Flare Forecasting Model Based on Data Mining Method |
| title_full | Full-Disk Solar Flare Forecasting Model Based on Data Mining Method |
| title_fullStr | Full-Disk Solar Flare Forecasting Model Based on Data Mining Method |
| title_full_unstemmed | Full-Disk Solar Flare Forecasting Model Based on Data Mining Method |
| title_short | Full-Disk Solar Flare Forecasting Model Based on Data Mining Method |
| title_sort | full disk solar flare forecasting model based on data mining method |
| url | http://dx.doi.org/10.1155/2019/5190353 |
| work_keys_str_mv | AT rongli fulldisksolarflareforecastingmodelbasedondataminingmethod AT yongdu fulldisksolarflareforecastingmodelbasedondataminingmethod |