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Investigating a Multi-Modal Attention-Based Deep-Learning Framework for Long-Term IMF Bz Forecasting Based on CME Kinematics and Solar Magnetogram Data.

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Title: Investigating a Multi-Modal Attention-Based Deep-Learning Framework for Long-Term IMF Bz Forecasting Based on CME Kinematics and Solar Magnetogram Data.
Authors: Dani, Tiar1,2 (AUTHOR), Winarko, Edi1 (AUTHOR) ewinarko@ugm.ac.id, Heryawan, Lukman1 (AUTHOR), Muhamad, Johan2 (AUTHOR), Nuraeni, Fitri2,3 (AUTHOR), Pangestu, Ayu Dyah2,4 (AUTHOR)
Source: Solar Physics. Feb2026, Vol. 301 Issue 2, p1-37. 37p.
Database: Academic Search Ultimate
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Header DbId: asn
DbLabel: Academic Search Ultimate
An: 192346580
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Investigating a Multi-Modal Attention-Based Deep-Learning Framework for Long-Term IMF Bz Forecasting Based on CME Kinematics and Solar Magnetogram Data.
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  Data: <searchLink fieldCode="JN" term="%22Solar+Physics%22">Solar Physics</searchLink>. Feb2026, Vol. 301 Issue 2, p1-37. 37p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=192346580
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s11207-026-02629-x
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      – Code: eng
        Text: English
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        PageCount: 37
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      – TitleFull: Investigating a Multi-Modal Attention-Based Deep-Learning Framework for Long-Term IMF Bz Forecasting Based on CME Kinematics and Solar Magnetogram Data.
        Type: main
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          Name:
            NameFull: Dani, Tiar
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            NameFull: Winarko, Edi
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            NameFull: Heryawan, Lukman
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            NameFull: Muhamad, Johan
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            NameFull: Nuraeni, Fitri
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            – D: 01
              M: 02
              Text: Feb2026
              Type: published
              Y: 2026
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              Value: 301
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            – TitleFull: Solar Physics
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