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Dataset for "Forecasting Coastal Hypoxia Using a Blend of Numeric and Artificial Intelligence Models"
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| Type: | Resource | |
| Storage: | The size of this resource is 1.4 GB | |
| Created: | Nov 01, 2023 at 9:04 p.m. (UTC) | |
| Last updated: | Jul 09, 2024 at 10:30 p.m. (UTC) | |
| Citation: | See how to cite this resource | |
| Content types: | Multidimensional Content |
| Sharing Status: | Public |
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| Views: | 1277 |
| Downloads: | 3 |
| +1 Votes: | 1 other +1 this |
| Comments: | No comments (yet) |
Abstract
Dataset (splitted into 14 files due to file size limitation) for training, validating, and evaluating AI model which was developed for daily hypoxia prediction in the Louisiana-Texas shelf. The dateset is derived from a coupled hydrodynamic-biogeochemical model embedded in the Regional Ocean Modeling System. External dataset from three independent hydrodynamic forecast products: HYCOM, NEMO, and FVCOM.
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How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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