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A New Hybrid Approach for Wind Speed Prediction Using Fast Block Least Mean Square Algorithm and Artificial Neural Network

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dc.contributor.authorFilik, Ümmühan Başaran
dc.contributor.orcid0000-0002-0715-821X
dc.date.accessioned2025-11-13T11:32:24Z
dc.date.issued2016-01-01
dc.identifier.doihttps://doi.org/10.1155/2016/8395751
dc.identifier.endpage9
dc.identifier.issn1024-123X
dc.identifier.openalexW2543122431
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11421/7132
dc.identifier.urihttps://doi.org/10.1155/2016/8395751
dc.identifier.volume2016
dc.language.isoen
dc.relation.ispartofMathematical Problems in Engineering
dc.rightsopenAccess
dc.subjectMean squared error
dc.subjectArtificial neural network
dc.subjectAlgorithm
dc.subjectConvergence (economics)
dc.subjectWind speed
dc.subjectBlock (permutation group theory)
dc.subjectComputer science
dc.subjectRate of convergence
dc.subjectData set
dc.subjectMathematics
dc.subjectArtificial intelligence
dc.subjectStatistics
dc.subjectKey (lock)
dc.subjectMeteorology
dc.subject.sdg7
dc.titleA New Hybrid Approach for Wind Speed Prediction Using Fast Block Least Mean Square Algorithm and Artificial Neural Network
dc.typeArticle
dspace.entity.typePublication
local.authorid.openalexA5043720840

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