Estimated nitrate d15N modeled using an ensemble of artificial neural networks (EANNs)
Estimated nitrate d15N modeled using an ensemble of artificial neural networks (EANNs)
Date
2019-06-17
Authors
Rafter, Patrick
Bagnell, Aaron
DeVries, Timothy
Marconi, Dario
Bagnell, Aaron
DeVries, Timothy
Marconi, Dario
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Date Created
2019-05-28
Location
westlimit: -180; southlimit: -79.5; eastlimit: 180; northlimit: 83.5
DOI
10.1575/1912/bco-dmo.768655.1
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Abstract
We utilize an ensemble of artificial neural networks (EANNs) to interpolate our global ocean nitrate d15N database, producing complete 3D maps of the data. By utilizing an artificial neural network (ANN), a machine learning approach that effectively identifies nonlinear relationships between a target variable (the isotopic dataset) and a set of input features (other available ocean datasets), we can fill holes in our data sampling coverage of nitrate d15N.
For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/768655
Description
Dataset: Global model nitrate d15N
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Citation
Rafter, P., Bagnell, A., DeVries, T., & Marconi, D. (2019). Estimated nitrate d15N modeled using an ensemble of artificial neural networks (EANNs). Biological and Chemical Oceanography Data Management Office. https://doi.org/10.1575/1912/bco-dmo.768655.1
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