Genetic programming model for long-term forecasting of electric power demand

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dc.contributor.authorLee, DGko
dc.contributor.authorLee, BWko
dc.contributor.authorChang, Soon-Heungko
dc.date.accessioned2013-02-27T22:43:03Z-
dc.date.available2013-02-27T22:43:03Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued1997-01-
dc.identifier.citationELECTRIC POWER SYSTEMS RESEARCH, v.40, no.1, pp.17 - 22-
dc.identifier.issn0378-7796-
dc.identifier.urihttp://hdl.handle.net/10203/71273-
dc.description.abstractGenetic programming (GP) involves finding both the functional form and the numeric coefficients for the model. So it does not require the assumption of any functional relationship between dependent and independent variables. The use of GP for solving long-term forecasting of the electric power demand problem is discussed; several cases which have different combinations of terminal sets and functional sets were investigated. The results of annual forecasting of electric power demand are presented for various cases using the GP model. The GP model is compared with the regression model. (C) 1997 Elsevier Science S.A.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE SA LAUSANNE-
dc.titleGenetic programming model for long-term forecasting of electric power demand-
dc.typeArticle-
dc.identifier.wosidA1997WX91300003-
dc.identifier.scopusid2-s2.0-0030716641-
dc.type.rimsART-
dc.citation.volume40-
dc.citation.issue1-
dc.citation.beginningpage17-
dc.citation.endingpage22-
dc.citation.publicationnameELECTRIC POWER SYSTEMS RESEARCH-
dc.contributor.localauthorChang, Soon-Heung-
dc.contributor.nonIdAuthorLee, DG-
dc.contributor.nonIdAuthorLee, BW-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorforecasting-
dc.subject.keywordAuthorgenetic programming-
dc.subject.keywordAuthorelectric demand-
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