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dc.contributor.authorAllen, Michael
dc.contributor.authorPreis, Ami
dc.contributor.authorIqbal, Mudasser
dc.contributor.authorPerelman, Lina Sela
dc.contributor.authorWhittle, Andrew
dc.date.accessioned2017-03-15T16:39:04Z
dc.date.available2017-03-15T16:39:04Z
dc.date.issued2014-12
dc.date.submitted2014-11
dc.identifier.issn1364-8152
dc.identifier.urihttp://hdl.handle.net/1721.1/107418
dc.description.abstractWater distribution systems (WDS) are complex pipe networks with looped and branching topologies that often comprise thousands to tens of thousands of links and nodes. This work presents a generic framework for improved analysis and management of WDS by partitioning the system into smaller (almost) independent sub-systems with balanced loads and minimal number of interconnections. This paper compares the performance of three classes of unsupervised learning algorithms from graph theory for practical sub-zoning of WDS: (1) Global clustering – a bottom-up algorithm for clustering n objects with respect to a similarity function, (2) Community structure – a bottom-up algorithm based on the property of network modularity, which is a measure of the quality of network partition to clusters versus randomly generated graph with respect to the same nodal degree, and (3) Graph partitioning – a flat partitioning algorithm for dividing a network with n nodes into k clusters, such that the total weight of edges crossing between clusters is minimized and the loads of all the clusters are balanced. The algorithms are adapted to WDS to provide a practical decision support tool for water utilities. Visual qualitative and quantitative measures are proposed to evaluate models' performance. The three methods are applied for two large-scale water distribution systems serving heavily populated areas in Singapore.en_US
dc.description.sponsorshipMIT-Technion Fellowshipen_US
dc.description.sponsorshipSingapore-MIT Alliance for Research and Technology (SMART)en_US
dc.language.isoen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.envsoft.2014.11.025en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourceProf. Whittle via Anne Grahamen_US
dc.titleAutomated Sub-Zoning of Water Distribution Systemsen_US
dc.typeArticleen_US
dc.identifier.citationSela Perelman, Lina et al. “Automated Sub-Zoning of Water Distribution Systems.” Environmental Modelling & Software 65 (2015): 1–14.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.contributor.approverWhittle, Andrew Jen_US
dc.contributor.mitauthorPerelman, Lina Sela
dc.contributor.mitauthorWhittle, Andrew
dc.relation.journalEnvironmental Modelling and Softwareen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsPerelman, Lina Sela; Allen, Michael; Preis, Ami; Iqbal, Mudasser; Whittle, Andrew J.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-5358-4140
mit.licensePUBLISHER_CCen_US


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