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dc.contributorEscuela de Ingenierias Industrial, Informática y Aeroespaciales_ES
dc.contributor.authorGarcía Gutiérrez, Adrián 
dc.contributor.authorDomínguez Fernández, Diego 
dc.contributor.authorLópez Rodríguez, Deibi 
dc.contributor.authorGonzalo de Grado, Jesús 
dc.contributor.otherFisica Aplicadaes_ES
dc.date2021
dc.date.accessioned2024-01-11T12:42:34Z
dc.date.available2024-01-11T12:42:34Z
dc.identifier.citationGarcía-Gutiérrez, A., Domínguez, D., López, D., & Gonzalo, J. (2021). Atmospheric boundary layer wind profile estimation using neural networks applied to lidar measurements. Sensors, 21(11), 3659.es_ES
dc.identifier.urihttps://hdl.handle.net/10612/17581
dc.description.abstract[EN] This paper introduces a new methodology for estimating the wind profile within the ABL (Atmospheric Boundary Layer) using a neural network and a single-point near-ground measurement. An important advantage of this solution when compared with others available in the literature is that it only requires near surface measurements for the prognosis once the neural network is trained. Another advantage is that it can be used to study the wind profile temporal evolution. This work uses data collected by a lidar sensor located at the Universidad de León (Spain). The neural network best configuration was determined using sensibility analyses. The result is a multilayer perceptron with three layers for each altitude: the input layer has six nodes for the last three measurements, the second has 128 nodes and the third consists of two nodes that provide u and v. The proposed method has better performance than traditional methods. The obtained wind profile information obtained is useful for multiple applications, such as preliminary calculations of the wind resource or CFD models.es_ES
dc.languageenges_ES
dc.publisherMDPIes_ES
dc.rightsAttribution 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectMeteorologíaes_ES
dc.subject.otherNeural networkes_ES
dc.subject.otherWind vertical profilees_ES
dc.subject.otherLidares_ES
dc.subject.otherAtmospheric boundary layeres_ES
dc.titleAtmospheric Boundary Layer Wind Profile Estimation Using Neural Networks Applied to Lidar Measurementses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doi10.3390/s21113659
dc.description.peerreviewedSIes_ES
dc.relation.projectIDUNLE15-EE-2977es_ES
dc.relation.projectIDUNLEes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.essn1424-8220
dc.journal.titleSensorses_ES
dc.volume.number21es_ES
dc.issue.number11es_ES
dc.page.initial3659es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES
dc.subject.unesco2509.08 Micrometeorologíaes_ES
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/21/11/3659


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Attribution 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution 4.0 Internacional