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Enhanced equal frequency partition method for the identification of a water demand system

dc.contributor.authorEscobet Canal, Antoni
dc.contributor.authorHuber Garrido, Rafael M.
dc.contributor.authorNebot Castells, M. Àngela
dc.contributor.authorCellier, François E.
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Minera, Industrial i TIC
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.coverage.spatialeast=-9.388059800000065; north=38.7990411; name=Tv. Munícipio 2, 2710-631 Sintra, Portugal
dc.date.accessioned2019-11-13T12:47:16Z
dc.date.available2019-11-13T12:47:16Z
dc.date.issued2000
dc.identifier.citationEscobet, A. [et al.]. Enhanced equal frequency partition method for the identification of a water demand system. A: AI, Simulation and Planning in High Autonomy Systems Conference. "AI, simulation and planning in high autonomy systems: [AIS 2000], March 6 - 8, 2000, Sheraton Tucson Hotel and Suites, Tucson, Arizona ". Sarjoughian,H.S.; Cellier, F.E.; Marefat, M.M.; Rozenblit, J.W. (eds.) Institute of Electrical and Electronics Engineers, 2000, p. 209-215.
dc.identifier.isbn1-56555-194-XX
dc.identifier.urihttp://hdl.handle.net/2117/172308
dc.description.abstractThis paper deals with unsupervised partitioning. A first goal of this paper is to present an enhancement to the Equal Frequency Partition (EFP) method that allows to reduce, to some extent, the main drawback of this classical classification method, i.e. the data distribution dependency. A second goal of this work is to use the Enhanced Equal Frequency Partition (EEFP) method within the discretization process of the Fuzzy Inductive Reasoning (FIR) methodology for the identification of a model of a water demand system. It is shown that use of the EEFP method allows to obtain more accurate FIR models of the water demand system, reducing the prediction errors.
dc.format.extent7 p.
dc.language.isoeng
dc.publisherSarjoughian,H.S.; Cellier, F.E.; Marefat, M.M.; Rozenblit, J.W. (eds.) Institute of Electrical and Electronics Engineers
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshFailure analysis (Engineering)
dc.subject.lcshWater -- Distribution
dc.subject.lcshControl theory
dc.subject.lcshInduction (Mathematics)
dc.subject.lcshError analysis (Mathematics)
dc.subject.otherUnsupervised partitioning
dc.subject.otherFuzzy inductive reasoning
dc.subject.otherWater demand system
dc.subject.otherControl theory
dc.titleEnhanced equal frequency partition method for the identification of a water demand system
dc.typeConference report
dc.subject.lemacAigua -- Distribució
dc.subject.lemacControl, Teoria de
dc.subject.lemacInducció (Matemàtica)
dc.subject.lemacAnàlisi d'error (Matemàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. SIC - Sistemes Intel·ligents de Control
dc.contributor.groupUniversitat Politècnica de Catalunya. SOCO - Soft Computing
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
local.identifier.drac2434203
dc.description.versionPostprint (author's final draft)
local.citation.authorEscobet, A.; Huber, R.; Nebot, M.; Cellier, F.
local.citation.contributorAI, Simulation and Planning in High Autonomy Systems Conference
local.citation.publicationNameAI, simulation and planning in high autonomy systems: [AIS 2000], March 6 - 8, 2000, Sheraton Tucson Hotel and Suites, Tucson, Arizona
local.citation.startingPage209
local.citation.endingPage215


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