Processing of Magnetotelluric Data Using Machine Learning Techniques

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dc.contributor.advisorMarcuello Pascual, Alejandro
dc.contributor.authorNocelo Sampedro, Paula
dc.date.accessioned2021-10-05T15:24:45Z
dc.date.available2021-10-05T15:24:45Z
dc.date.issued2021-02
dc.descriptionTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2021, Tutor: Alejandro Marcuello Pascualca
dc.description.abstractThis report is based on magnetotelluric (MT) data from the electromagnetic (EM) Earth field. The main objective is to analyze, reduce, and asses EM noise, coming from man-made technologies. To evaluate how to denoise MT data, a code is developed in Python, which uses the K-Means technique from machine learning. In the end, it is obtained a preliminary method to identify noise situations.ca
dc.format.extent5 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/180406
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Nocelo, 2021
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Física
dc.subject.classificationProspecció magnetotel·lúricacat
dc.subject.classificationAprenentatge automàticcat
dc.subject.classificationTreballs de fi de graucat
dc.subject.otherMagnetotelluric prospectingeng
dc.subject.otherMachine learningeng
dc.subject.otherBachelor's theseseng
dc.titleProcessing of Magnetotelluric Data Using Machine Learning Techniqueseng
dc.typeinfo:eu-repo/semantics/bachelorThesisca

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