<p>A resilient wet prairie? Predicting shallow groundwater levels changes using machine learning</p>

Enrique Gomezdelcampo; Priyanka R. More; Sheila J.  Roberts

doi:10.7490/f1000research.1115971.1

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Gomezdelcampo E, More PR and Roberts SJ. A resilient wet prairie? Predicting shallow groundwater levels changes using machine learning [version 1; not peer reviewed]. F1000Research 2018, 7:1300 (poster) (https://doi.org/10.7490/f1000research.1115971.1)

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A resilient wet prairie? Predicting shallow groundwater levels changes using machine learning

Enrique Gomezdelcampo¹, Priyanka R. More, Sheila J. Roberts

Published 15 Aug 2018 (https://doi.org/10.7490/f1000research.1115971.1)

Author Affiliations

¹ Bowling Green State University, USA

Copyright © 2018 Gomezdelcampo E et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 15 Aug 2018

A resilient wet prairie? Predicting shallow groundwater levels changes using machine learning
[version 1; not peer reviewed]

Enrique Gomezdelcampo¹, Priyanka R. More, Sheila J. Roberts

Author Affiliations

¹ Bowling Green State University, USA

Presented at

103rd Ecological Society Of America (ESA) Annual Meeting 2018

Abstract

Competing Interests

No competing interests were disclosed

Keywords

wetlands, wet prairie, shallow groundwater, hydrologic modeling, Neural Networks, ANN

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