Ensemble decision tree models using RUSBoost for estimating risk of iron failure in drinking water distribution systems

Mounce, S.R. orcid.org/0000-0003-0742-0908, Ellis, K., Edwards, J.M. et al. (3 more authors) (2017) Ensemble decision tree models using RUSBoost for estimating risk of iron failure in drinking water distribution systems. Water Resources Management, 31 (5). pp. 1575-1589. ISSN 0920-4741

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © The Author(s) 2017. This is an author produced version of a paper subsequently published in Water Resources Management. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Water distribution systems; Water Quality; Iron; Machine Learning; Ensemble Decision Trees; RUSBoost
Dates:
  • Accepted: 15 February 2017
  • Published (online): 9 March 2017
  • Published: March 2017
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield)
Funding Information:
FunderGrant number
DWYR CYMRU WELSH WATERNONE
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/I029346/1
Depositing User: Symplectic Sheffield
Date Deposited: 22 Feb 2017 10:15
Last Modified: 03 Nov 2017 02:49
Published Version: https://doi.org/10.1007/s11269-017-1595-8
Status: Published
Publisher: Springer Verlag
Refereed: Yes
Identification Number: https://doi.org/10.1007/s11269-017-1595-8

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