Modeling Bottom Dissolved Oxygen on the East China Sea Shelf Using Interpretable Machine Learning
Monitoring bottom dissolved oxygen (DO) is crucial for understanding hypoxia, a threat to marine ecosystems and fisheries. However, traditional observations are limited in spatiotemporal coverage, while numerical models consume tremendous computing resources. This study develops an interpretable mac...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/13/2/359 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Be the first to leave a comment!