dc.contributor.author | Allen, Michael | |
dc.contributor.author | Preis, Ami | |
dc.contributor.author | Iqbal, Mudasser | |
dc.contributor.author | Perelman, Lina Sela | |
dc.contributor.author | Whittle, Andrew | |
dc.date.accessioned | 2017-03-15T16:39:04Z | |
dc.date.available | 2017-03-15T16:39:04Z | |
dc.date.issued | 2014-12 | |
dc.date.submitted | 2014-11 | |
dc.identifier.issn | 1364-8152 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/107418 | |
dc.description.abstract | Water 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.sponsorship | MIT-Technion Fellowship | en_US |
dc.description.sponsorship | Singapore-MIT Alliance for Research and Technology (SMART) | en_US |
dc.language.iso | en_US | |
dc.publisher | Elsevier | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.envsoft.2014.11.025 | en_US |
dc.rights | Creative Commons Attribution-NonCommercial-NoDerivs License | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.source | Prof. Whittle via Anne Graham | en_US |
dc.title | Automated Sub-Zoning of Water Distribution Systems | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Sela Perelman, Lina et al. “Automated Sub-Zoning of Water Distribution Systems.” Environmental Modelling & Software 65 (2015): 1–14. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering | en_US |
dc.contributor.approver | Whittle, Andrew J | en_US |
dc.contributor.mitauthor | Perelman, Lina Sela | |
dc.contributor.mitauthor | Whittle, Andrew | |
dc.relation.journal | Environmental Modelling and Software | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Perelman, Lina Sela; Allen, Michael; Preis, Ami; Iqbal, Mudasser; Whittle, Andrew J. | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-5358-4140 | |
mit.license | PUBLISHER_CC | en_US |