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dc.contributorRojas Bartomeus, Pol
dc.contributorMorros Rubió, Josep Ramon
dc.contributor.authorVacas Vargas, Alberto
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2022-01-19T13:26:11Z
dc.date.issued2021-06-29
dc.identifier.urihttp://hdl.handle.net/2117/360013
dc.description.abstractBanking is becoming branchless, contemporary and digital at a very fast pace. As banks compete to gain a competitive advantage, the need to manage large amounts of data and analytics becomes more relevant as well as the optimization of resources. Within this sector, one of the things they want to optimize is the volume of cash that different tellers will need to handle customer demand. And it is precisely on this aspect that this thesis will be based: to predict the volume of money needed to cover all the withdrawals demanded by customers at the ATMs using different machine learning models.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
dc.subject.lcshRegression analysis
dc.subject.lcshMachine learning
dc.subject.lcshCluster analysis
dc.subject.otherClustering
dc.subject.othermachine learning
dc.subject.otherregression
dc.titleCash demand forecasting for ATMs
dc.typeMaster thesis
dc.subject.lemacAnàlisi de regressió
dc.subject.lemacAprenentatge automàtic
dc.subject.lemacAnàlisi de conglomerats
dc.identifier.slugETSETB-230.161183
dc.rights.accessRestricted access - author's decision
dc.date.lift10000-01-01
dc.date.updated2021-07-22T05:50:53Z
dc.audience.educationlevelMàster
dc.audience.mediatorEscola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona
dc.audience.degreeMÀSTER UNIVERSITARI EN TECNOLOGIES AVANÇADES DE TELECOMUNICACIÓ (Pla 2019)


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