1. Электронный научный архив УрФУ
  2. 00. Общеуниверситетские коллекции
  3. Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC
Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/75739
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dc.contributor.authorChernykh, I.en
dc.contributor.authorChechushkov, D.en
dc.contributor.authorPanikovskaya, T.en
dc.date.accessioned2019-07-22T06:48:24Z-
dc.date.available2019-07-22T06:48:24Z-
dc.date.issued2014-
dc.identifier.citationChernykh I. The prediction of electric energy consumption using an artificial neural network / I. Chernykh, D. Chechushkov, T. Panikovskaya // WIT Transactions on Ecology and the Environment. — 2014. — Vol. 190 VOLUME 1. — P. 109-117.en
dc.identifier.issn1743-3541-
dc.identifier.otherhttp://www.witpress.com/Secure/elibrary/papers/EQ14/EQ14012FU1.pdfpdf
dc.identifier.other1good_DOI
dc.identifier.other0d8f5e43-2a7d-4fc5-ba31-96f8670c75d3pure_uuid
dc.identifier.otherhttp://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=84897841114m
dc.identifier.urihttp://elar.urfu.ru/handle/10995/75739-
dc.description.abstractThis paper presents the results of the studies on forecasting the electrical loads for a megapolis district with the use of artificial neural networks (ANN) as one of the most accomplished and promising solutions to this challenge. A theoretical approach to the issue is combined with the results of experimental studies using real schedules. © 2014 WIT Press.en
dc.description.sponsorshipInternational Journal of Safety and Security Engineering;International Journal of Sustainable Development and Planning;WIT Transactions on Ecology and the Environmenten
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherWITPressen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceWIT Transactions on Ecology and the Environmenten
dc.subjectARTIFICIAL NEURAL NETWORKen
dc.subjectELECTRICAL LOADSen
dc.subjectUPDATED INPUT DATAen
dc.subjectARTIFICIAL NEURAL NETWORKen
dc.subjectENERGY USEen
dc.subjectMEGACITYen
dc.subjectPREDICTIONen
dc.titleThe prediction of electric energy consumption using an artificial neural networken
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.conference.name1st International Conference on Energy Production and Management in the 21st Century: The Quest for Sustainable Energyen
dc.conference.date23 April 2014 through 25 April 2014-
dc.identifier.doi10.2495/EQ140121-
dc.identifier.scopus84897841114-
local.affiliationDepartment of High Voltage Engineering, Ural Federal University, Russian Federationen
local.affiliationDepartment of Automated Electric Systems, Ural Federal University, Russian Federationen
local.contributor.employeeЧерных Илья Викторовичru
local.contributor.employeeЧечушков Дмитрий Александровичru
local.contributor.employeeПаниковская Татьяна Юрьевнаru
local.description.firstpage109-
local.description.lastpage117-
local.volume190 VOLUME 1-
local.identifier.pure379160-
local.identifier.eid2-s2.0-84897841114-
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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