Reference:Reference-021317: Difference between revisions
From CSDMS
Created page with "{{CSDMS reference template cargo |DOIentry=10.2166/nh.2022.044 }} {{RefsInt1 |FeatureRef=No |PublicationClusterID=0 |MS_PublicationClusterID=0 |Semantic_ID=3d8c3253603b3d82f4af74b211f843e649394d7e |PublicationWhatKindOf=a module application description |PublicationHPCCYesno=No |PublicationNrofModels=a single module }} {{RefsInt2 |PublicationMultipleModelsCargo=HBV }} {{RefsInt3}}" |
Bot: Automated import of articles *** existing text overwritten *** |
||
| Line 1: | Line 1: | ||
{{ | {{BibEntryCargo | ||
| | |Firstname=Volpi, Elena; Kim, Jong Suk; Jain, Shaleen; Shrestha, Sangam; de Moura, Carolina Natel; Seibert, Jan; Marco Detzel, Daniel Henrique; | ||
|BibType=bookSection | |||
|Title=Evaluating the long short-term memory (LSTM) network for discharge prediction under changing climate conditions | |||
|Year=2024-06-15 | |||
|Journal=None | |||
|Booktitle=Artificial Intelligence in Hydrology | |||
|Volume=None | |||
|Pages=None | |||
|URL=https://iwaponline.com/ebooks/book/925/chapter/3763414/Evaluating-the-long-short-term-memory-LSTM-network | |||
|DOI=None | |||
|Note=Auto downloaded ref at: 2024-08-29 | |||
}} | }} | ||
{{RefsInt1 | {{RefsInt1 | ||
| Line 8: | Line 18: | ||
|Semantic_ID=3d8c3253603b3d82f4af74b211f843e649394d7e | |Semantic_ID=3d8c3253603b3d82f4af74b211f843e649394d7e | ||
|PublicationWhatKindOf=a module application description | |PublicationWhatKindOf=a module application description | ||
|PublicationNrofModels=a single module | |||
|PublicationHPCCYesno=No | |PublicationHPCCYesno=No | ||
}} | }} | ||
{{RefsInt2 | {{RefsInt2 | ||
|PublicationMultipleModelsCargo=HBV | |PublicationMultipleModelsCargo=HBV | ||
}} | }} | ||
{{RefsInt3}} | {{RefsInt3 | ||
|PublicationAnimationsCargo=None | |||
}} | |||
Revision as of 08:41, 30 August 2024
| Author(s) | Volpi, Elena; Kim, Jong Suk; Jain, Shaleen; Shrestha, Sangam; de Moura, Carolina Natel; Seibert, Jan; Marco Detzel, Daniel Henrique; |
| BibType | bookSection |
| Title | Evaluating the long short-term memory (LSTM) network for discharge prediction under changing climate conditions |
| Editors | |
| Year | 2024-06-15 |
| Journal | None |
| Booktitle | Artificial Intelligence in Hydrology |
| Volume | None |
| Pages | None |
| URL | https://iwaponline.com/ebooks/book/925/chapter/3763414/Evaluating-the-long-short-term-memory-LSTM-network |
| DOI | None |
| ISBN | |
| Note | Auto downloaded ref at: 2024-08-29
|
| |
|
| Feature reference | No |
| PublicationClusterID | 0 |
| MS_PublicationClusterID | 0 |
| Semantic_ID | 3d8c3253603b3d82f4af74b211f843e649394d7e |
| Nr of citations | 6 |
| 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: |
|
| Model(s) discussed: | HBV
|
