Reference:Reference-032227: Difference between revisions
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|Title=Deep Learning for Solar Irradiance Nowcasting: A Comparison of a Recurrent Neural Network and Two Traditional Methods | |Title=Deep Learning for Solar Irradiance Nowcasting: A Comparison of a Recurrent Neural Network and Two Traditional Methods | ||
|Year=2021 | |Year=2021 | ||
|Journal= | |Journal= | ||
|Booktitle=Computational Science – ICCS 2021 | |Booktitle=Computational Science – ICCS 2021 | ||
|Volume=12746 | |Volume=12746 | ||
|Pages=309–322 | |Pages=309–322 | ||
|URL=https://link.springer.com/10.1007/978-3-030-77977-1_24 | |URL=https://link.springer.com/10.1007/978-3-030-77977-1_24 | ||
|DOI= | |DOI= | ||
|Note=Auto downloaded ref at: 2024-09-08 | |Note=Auto downloaded ref at: 2024-09-08 | ||
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Latest revision as of 14:21, 12 November 2024
| Author(s) | Paszynski, Maciej; Kranzlmüller, Dieter; Krzhizhanovskaya, Valeria V.; Dongarra, Jack J.; Sloot, Peter M.A.; Knol, Dennis; de Leeuw, Fons; Meirink, Jan Fokke; | |
| BibType | bookSection | |
| Title | Deep Learning for Solar Irradiance Nowcasting: A Comparison of a Recurrent Neural Network and Two Traditional Methods | |
| Editors | ||
| Year | 2021 | |
| Journal | ||
| Booktitle | Computational Science – ICCS 2021 | |
| Volume | 12746 | |
| Pages | 309–322 | |
| URL | https://link.springer.com/10.1007/978-3-030-77977-1_24 | |
| DOI | ||
| ISBN | ||
| Note | Auto downloaded ref at: 2024-09-08
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| Which groups | ||
| Feature reference | No | |
| PublicationClusterID | 0 | |
| MS_PublicationClusterID | 0 | |
| Semantic_ID | efaec4c2eea709c9d7301be60899a865a91a5eee | |
| Nr of citations | 5 | |
| Sort of publication | a module application description | |
| Sort of model publication | a single module | |
| Is the CSDMS HPC used | No | |
| If HPC is used, for what project was it?: | ||
| Associated simulation movie if any: |
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| Model(s) discussed: | WRF
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