Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/126969
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dc.contributor.advisorSanz-Solé, Marta-
dc.contributor.authorGnutti Sandiumenge, Gerard-
dc.date.accessioned2018-12-14T11:45:31Z-
dc.date.available2018-12-14T11:45:31Z-
dc.date.issued2018-06-27-
dc.identifier.urihttp://hdl.handle.net/2445/126969-
dc.descriptionTreballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2018, Director: Marta Sanzca
dc.description.abstract[en] There are many situations where we want to model a certain phenomenon but it’s impossible to know exactly its evolution over time. For example, we can’t find a differential equation to model the position of a pollen grain suspended in water. It is considered that these phenomena follow a certain randomness. As it is not useful to model it using deterministic models, we need stochastic tools. The purpose of this work is to introduce us in stochastic modeling. We’ll do it by studying a specific case where stochastic models are used, queuing theory.ca
dc.format.extent56 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isocatca
dc.rightscc-by-nc-nd (c) Gerard Gnutti Sandiumenge, 2018-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Matemàtiques-
dc.subject.classificationTeoria de cuesca
dc.subject.classificationTreballs de fi de grau-
dc.subject.classificationProcessos estocàsticsca
dc.subject.classificationProcessos de Markovca
dc.subject.otherQueuing theoryen
dc.subject.otherBachelor's theses-
dc.subject.otherStochastic processesen
dc.subject.otherMarkov processesen
dc.titleProcessos estocàstics aplicats a teoria de cuesca
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Treballs Finals de Grau (TFG) - Matemàtiques

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