dc.creator | Petković, Dalibor | |
dc.creator | Nikolić, Vlastimir | |
dc.creator | Mitić, Vojislav V. | |
dc.creator | Kocić, Ljubiša | |
dc.date.accessioned | 2018-12-18T23:34:07Z | |
dc.date.available | 2019-01-17 | |
dc.date.issued | 2017 | |
dc.identifier.issn | 0955-5986 | |
dc.identifier.uri | https://dais.sanu.ac.rs/123456789/4612 | |
dc.description.abstract | Since 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 interpolation | en |
dc.language | en | |
dc.publisher | Elsevier | |
dc.rights | embargoedAccess | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.source | Flow Measurement and Instrumentation | en |
dc.subject | wind speed | |
dc.subject | fractal interpolation | |
dc.subject | soft computing | |
dc.subject | prediction | |
dc.title | Estimation of fractal representation of wind speed fluctuation by artificial neural network with different training algorothms | en |
dc.type | article | |
dc.rights.license | BY-NC-ND | |
dcterms.abstract | Николић, Властимир; Митић, Војислав В.; Коцић, Љубиша; Петковић, Далибор; | |
dc.citation.spage | 172 | |
dc.citation.epage | 176 | |
dc.citation.volume | 54 | |
dc.identifier.wos | 000401377500017 | |
dc.identifier.doi | 10.1016/j.flowmeasinst.2017.01.007 | |
dc.identifier.scopus | 2-s2.0-85010208986 | |
dc.description.other | This 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] | |
dc.type.version | acceptedVersion | |
dc.identifier.fulltext | https://dais.sanu.ac.rs/bitstream/id/14405/petkovi2017.pdf | |
dc.identifier.rcub | https://hdl.handle.net/21.15107/rcub_dais_4612 | |