Ellis, K., Mounce, S.R., Edwards, J. et al. (3 more authors) (2015) Interpreting and estimating the risk of iron failures. In: Procedia Engineering. Computing and Control for the Water Industry (CCWI2015) Sharing the best practice in water management , pp. 299-308.
Abstract
Metals and particulates accumulate in the distribution system and are mobilised by hydraulic events which can result in discolouration and exceedance of regulatory standards. Traditional decision tools for targeting preventive work are single parameter, based for example on proportion of unlined iron pipe or the number of customer contacts per district metering area (DMA). We show that this approach is too simplistic and propose a multivariate Decision Tree process, using the Random Under-Sampling ensemble method. The outputs gave a classification of High or Low risk per DMA. Initial findings demonstrate an 80 % success rate in identifying high risk DMAs across the supply area for a UK water company.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license |
Keywords: | Decision Trees; District metering areas; Geographical Information Systems; Iron; Self-organising maps; Water quality |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Jan 2016 11:09 |
Last Modified: | 22 Jan 2016 11:09 |
Published Version: | http://dx.doi.org/10.1016/j.proeng.2015.08.889 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.proeng.2015.08.889 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:94031 |