BCO-DMO BlogDataset: Global model dissolved Zn
Data Citation:
DeVries, T. (2019) Global estimated dissolved zinc (Zn) using an ensemble of artificial neural networks. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 2) Version Date 2019-07-26 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/773657 [access date]
Terms of Use
This dataset is licensed under Creative Commons Attribution 4.0.
If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.
Spatial Extent: N:83.5 E:178.5 S:-77.5 W:-178.5
Project:
Collaborative research: Combining models and observations to constrain the marine iron cycle
(Fe Cycle Models and Observations)
Principal Investigator:
Timothy DeVries (University of California-Santa Barbara, UCSB)
BCO-DMO Data Manager:
Shannon Rauch (Woods Hole Oceanographic Institution, WHOI BCO-DMO)
Version:
2
Version Date:
2019-07-26
Restricted:
No
Validated:
Yes
Current State:
Final no updates expected
Global estimated dissolved zinc (Zn) using an ensemble of artificial neural networks
Abstract:
Dissolved zinc (Zn) concentration map modeled by means of ensemble artificial neural network. The ensemble consists of 100 neural networks each of which was trained by using a different randomly-selected 70% of observational dataset and the reported means and standard deviations are those calculated among the members of the ensemble.
©2024 Biological and Chemical Oceanography Data Management Office.
