A Machine Learning (kNN) Approach to Predicting Global Seafloor Total Organic Carbon-Reference-Cited by-同舟云学术

A Machine Learning (kNN) Approach to Predicting Global Seafloor Total Organic Carbon

Published:2019-01 Issue:1 Volume:33 Page:37-46
ISSN:0886-6236
Container-title:Global Biogeochemical Cycles
language:en
Short-container-title:Global Biogeochem. Cycles

Author:

Lee Taylor R.¹^ORCID,Wood Warren T.¹^ORCID,Phrampus Benjamin J.²^ORCID

Affiliation:

1. U.S. Naval Research Laboratory; John C. Stennis Space Center; Hancock County MS USA

2. ASEE Postdoctoral Program, U.S. Naval Research Laboratory; John C. Stennis Space Center; Hancock County MS USA

Funder

U.S. Naval Research Laboratory base program

Publisher

American Geophysical Union (AGU)

Subject

Atmospheric Science,General Environmental Science,Environmental Chemistry,Global and Planetary Change

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1029/2018GB005992/fullpdf

Reference26 articles.

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4. Aliphatic lipids in recent sediments of the Fram Strait/Yermak Plateau (Arctic Ocean): Composition, sources and transport processes;Birgel;Marine Chemistry,2004

5. Preservation of organic matter in marine sediments: Controls, mechanisms, and an imbalance in sediment organic carbon budgets?;Burdige;Chemical Reviews,2007

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