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dc.creatorPetković, Dalibor
dc.creatorNikolić, Vlastimir
dc.creatorMitić, Vojislav V.
dc.creatorKocić, Ljubiša
dc.date.accessioned2018-12-18T23:34:07Z
dc.date.available2019-01-17
dc.date.issued2017
dc.identifier.issn0955-5986
dc.identifier.urihttp://dais.sanu.ac.rs/123456789/4612
dc.description.abstractSince the wind speed fluctuation could cause large instability in wind energy systems it is crucial to develop a method for precise estimation of the wind speed fluctuation. Fractal interpolation of the wind speed could be used to improve the accuracy of the estimation of the wind speed fluctuation. Based on the self-similarity feature, the fractal interpolation could be established from internal to external interval. In this article fractal interpolation was used to improve the wind speed fluctuation estimation by soft computing methods. Artificial neural network (ANN) with different training algorithms were used in order to estimate the wind speed fluctuation based on the fractal interpolationen
dc.languageen
dc.publisherElsevier
dc.rightsembargoedAccess
dc.sourceFlow Measurement and Instrumentationen
dc.subjectwind speed
dc.subjectfractal interpolation
dc.subjectsoft computing
dc.subjectprediction
dc.titleEstimation of fractal representation of wind speed fluctuation by artificial neural network with different training algorothmsen
dc.typearticle
dc.rights.licenseBY-NC-ND
dcterms.abstractНиколић, Властимир; Митић, Војислав В.; Коцић, Љубиша; Петковић, Далибор;
dc.citation.spage172
dc.citation.epage176
dc.citation.volume54
dc.identifier.wos000401377500017
dc.identifier.doi10.1016/j.flowmeasinst.2017.01.007
dc.identifier.scopus2-s2.0-85010208986
dc.description.otherThis is the peer-reviewed version of the article: Petković, D., Nikolić, V., Mitić, V.V., Kocić, L., 2017. Estimation of fractal representation of wind speed fluctuation by artificial neural network with different training algorothms. Flow Measurement and Instrumentation 54, 172–176. [https://doi.org/10.1016/j.flowmeasinst.2017.01.007]
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