Power Grid Load Forecasting Using a CNN-LSTM Network Based on a Multi-Modal Attention Mechanism.
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| Title: | Power Grid Load Forecasting Using a CNN-LSTM Network Based on a Multi-Modal Attention Mechanism. |
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| Authors: | Guo, Wangyong1, Liu, Shijin1,2, Weng, Liguo1,2, 002311@nuist.edu.cn, Liang, Xingyu2 |
| Source: | Applied Sciences (2076-3417); Mar2025, Vol. 15 Issue 5, p2435, 24p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 183645098 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/app15052435 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 2435 Titles: – TitleFull: Power Grid Load Forecasting Using a CNN-LSTM Network Based on a Multi-Modal Attention Mechanism. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Guo, Wangyong – PersonEntity: Name: NameFull: Liu, Shijin – PersonEntity: Name: NameFull: Weng, Liguo – PersonEntity: Name: NameFull: Liang, Xingyu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20763417 Numbering: – Type: volume Value: 15 – Type: issue Value: 5 Titles: – TitleFull: Applied Sciences (2076-3417) Type: main |
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