Mostra el registre d'ítem simple

dc.contributorRego, Erik
dc.contributor.authorBlanch Urbán, Eduard
dc.coverage.spatialeast=-3.7071990966796875; north=40.41976938144622; name=Callao, 28013 Madrid, Espanya
dc.date.accessioned2016-01-28T20:20:33Z
dc.date.available2016-01-28T20:20:33Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/2117/82251
dc.description.abstractThe main objective in this research is to predict day-ahead prices using ARMA. Box and Jenkins developed a regression model to identify, assess and diagnose dynamic time series models in which the time variable plays a key role. In the area of EPF, several studies have already been conducted to estimate prices by ARMA: in some cases ARMA is combined with GARCH using a wavelet transform, in others a hybrid model with Radial Basis Function Neural Networks (RBFN) or with Support Vector Regression (SVR) is performed, and also a single ARIMA or the addition of a Transfer Function and Dynamic Regression have been used.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.publisherUniversidade de São Paulo
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Economia i organització d'empreses
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística
dc.subject.lcshElectricity -- Rates -- Forecasting
dc.subject.lcshEconomic forecasting
dc.subject.lcshRegression analysis
dc.titleForecasting day ahead electricity price using ARMA methods
dc.typeBachelor thesis
dc.subject.lemacElectricitat -- Tarifes -- Previsió
dc.subject.lemacPrevisió econòmica
dc.subject.lemacAnàlisi de regressió
dc.rights.accessOpen Access
dc.audience.educationlevelGrau
dc.audience.mediatorEscola Tècnica Superior d'Enginyeria Industrial de Barcelona
dc.contributor.covenanteeUniversidade de São Paulo
dc.description.mobilityOutgoing


Fitxers d'aquest items

Thumbnail

Aquest ítem apareix a les col·leccions següents

Mostra el registre d'ítem simple