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: Rong Li, Yong Du
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Advances in Astronomy
Online Access:http://dx.doi.org/10.1155/2019/5190353
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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
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1687-7977
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publishDate 2019-01-01
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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