Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/20832

Title: A benchmarking model for household water consumption based on adaptive logic networks
Authors: Chen, Xiaomin
Yang, Shuang-Hua
Yang, Lili
Chen, Xi
Keywords: Household water consumption
Socio-demographical factors
Adaptive logic networks
Issue Date: 2015
Publisher: © The Authors. Published by Elsevier
Citation: CHEN, X. ...et al., 2015. A benchmarking model for household water consumption based on adaptive logic networks. Procedia Engineering, 119(1), pp. 1391-1398.
Abstract: © 2015 The Authors. Published by Elsevier Ltd. Household water benchmarking is an important step in evaluating a household's water usage and comparing it with similar households. It can provide an indicator if a household consumes more water than usual during a certain period of time or some households consume more than other similar households in a particular region. This paper proposes a benchmarking model for household water consumption based on Adaptive Logic Networks (ALNs). Real world data collected by a water consumption monitoring system installed in Sosnowiec, Poland and Skiathos, Greece is respectively used to build a model for each city. The results indicate that the developed models can successfully prediction for a particular use purpose.
Description: This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY-NC-ND). Full details of this licence are available at: http://creativecommons.org/licenses/by-nc-nd/4.0/. It was presented at the 13th Computer Control for Water Industry Conference, (CCWI 201).
Sponsor: This work is part of the ISS-EWATUS project (issewatus.eu) and has been funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no (619228).
Version: Published
DOI: 10.1016/j.proeng.2015.08.998
URI: https://dspace.lboro.ac.uk/2134/20832
Publisher Link: http://dx.doi.org/10.1016/j.proeng.2015.08.998
Appears in Collections:Published Articles (Business School)

Files associated with this item:

File Description SizeFormat
Benchmaring model.pdfPublished version550 kBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.