The University of Southampton
University of Southampton Institutional Repository

A low-complexity machine learning nitrate loss predictive model – Towards proactive farm management in a networked catchment

A low-complexity machine learning nitrate loss predictive model – Towards proactive farm management in a networked catchment
A low-complexity machine learning nitrate loss predictive model – Towards proactive farm management in a networked catchment
2169-3536
Harris, Nicholas
237cfdbd-86e4-4025-869c-c85136f14dfd
Zia, Huma
74118b4c-35ab-44e8-a44f-daa4cc6f83e8
Merrett, Geoffrey
2d7935a7-acf7-41af-8951-a03a5be50781
Rivers, Mark
d77b505c-0318-4a77-bc88-a6fc38d38660
Harris, Nicholas
237cfdbd-86e4-4025-869c-c85136f14dfd
Zia, Huma
74118b4c-35ab-44e8-a44f-daa4cc6f83e8
Merrett, Geoffrey
2d7935a7-acf7-41af-8951-a03a5be50781
Rivers, Mark
d77b505c-0318-4a77-bc88-a6fc38d38660

Harris, Nicholas, Zia, Huma, Merrett, Geoffrey and Rivers, Mark (2019) A low-complexity machine learning nitrate loss predictive model – Towards proactive farm management in a networked catchment. IEEE Access. (doi:10.1109/ACCESS.2019.2901218).

Record type: Article
Text
FINAL Article - Accepted Manuscript
Available under License Creative Commons Attribution.
Download (421kB)

More information

Accepted/In Press date: 14 February 2019
e-pub ahead of print date: 18 February 2019

Identifiers

Local EPrints ID: 428537
URI: http://eprints.soton.ac.uk/id/eprint/428537
ISSN: 2169-3536
PURE UUID: 4e39e846-30ba-4f63-b77c-929fd2deb00c
ORCID for Nicholas Harris: ORCID iD orcid.org/0000-0003-4122-2219

Catalogue record

Date deposited: 01 Mar 2019 17:30
Last modified: 16 Mar 2024 02:45

Export record

Altmetrics

Contributors

Author: Nicholas Harris ORCID iD
Author: Huma Zia
Author: Geoffrey Merrett
Author: Mark Rivers

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×