Reference:Reference-025516: Difference between revisions
From CSDMS
Bot: Automated import of articles *** existing text overwritten *** |
m Text replacement - "|Semantic_ID=426dc20663fdf84fbf071c4bf4d83b15dd8a3182" to "|Semantic_ID=426dc20663fdf84fbf071c4bf4d83b15dd8a3182 |CorpusID=258880317" |
||
| Line 16: | Line 16: | ||
|PublicationClusterID=0 | |PublicationClusterID=0 | ||
|MS_PublicationClusterID=0 | |MS_PublicationClusterID=0 | ||
|Semantic_ID=426dc20663fdf84fbf071c4bf4d83b15dd8a3182 | |Semantic_ID=426dc20663fdf84fbf071c4bf4d83b15dd8a3182 |CorpusID=258880317 | ||
|PublicationWhatKindOf=a module application description | |PublicationWhatKindOf=a module application description | ||
|PublicationNrofModels=a single module | |PublicationNrofModels=a single module | ||
Revision as of 17:11, 30 September 2024
| Author(s) | Feng Chang, Christina; Astitha, Marina; Yuan, Yongping; Tang, Chunling; Vlahos, Penny; Garcia, Valerie; Khaira, Ummul; | |
| BibType | journalArticle | |
| Title | A New Approach to Predict Tributary Phosphorus Loads Using Machine Learning– and Physics-Based Modeling Systems | |
| Editors | ||
| Year | 2023-07 | |
| Journal | Artificial Intelligence for the Earth Systems | |
| Booktitle | None | |
| Volume | 2 | |
| Pages | None | |
| URL | https://journals.ametsoc.org/view/journals/aies/2/3/AIES-D-22-0049.1.xml | |
| DOI | 10.1175/AIES-D-22-0049.1 | |
| ISBN | ||
| Note | Auto downloaded ref at: 2024-09-04
| |
| |
||
| Highlighted paper on group site | ||
| Highlight text | ||
| Highlight image | ||
| Which groups | ||
| Feature reference | No | |
| PublicationClusterID | 0 | |
| MS_PublicationClusterID | 0 | |
| Semantic_ID | 426dc20663fdf84fbf071c4bf4d83b15dd8a3182 | |
| Nr of citations | 2 | |
| 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: | WRF
|
