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Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

2014-10-28Conference object Open access
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dc.contributor.authorMarques, Luís
dc.contributor.authorPinto, Tiago
dc.contributor.authorSousa, Tiago
dc.contributor.authorPraça, Isabel
dc.contributor.authorVale, Zita
dc.contributor.authorAbreu, Samuel L.
dc.date.accessioned2015-05-04T14:18:33Z
dc.date.available2015-05-04T14:18:33Z
dc.date.issued2014-10-28
dc.description.abstractThis paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.por
dc.identifier.urihttp://hdl.handle.net/10400.22/5888
dc.language.isoengpor
dc.publisherELECON Projectpor
dc.relation.ispartofseriesELECON;2014
dc.relation.publisherversionhttp://www.elecon.ipp.pt/images/Workshop2/Proceedings_elecon_2014.pdfpor
dc.subjectArtificial Neural Networkspor
dc.subjectData Miningpor
dc.subjectMachine Learningpor
dc.subjectSolar forecastingpor
dc.subjectSupport Vector Machinespor
dc.titleSolar Intensity Forecasting using Artificial Neural Networks and Support Vector Machinespor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceMagdeburg, Germanypor
oaire.citation.startPage83por
oaire.citation.titleSecond ELECON Workshop – Consumer control in Smart Gridspor
person.familyNamePinto
person.familyNamePraça
person.familyNameVale
person.givenNameTiago
person.givenNameIsabel
person.givenNameZita
person.identifierR-000-T7J
person.identifier299522
person.identifier632184
person.identifier.ciencia-id2414-9B03-C4BB
person.identifier.ciencia-idC710-4218-1BFF
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8248-080X
person.identifier.orcid0000-0002-2519-9859
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridT-2245-2018
person.identifier.ridK-8430-2014
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35219107600
person.identifier.scopus-author-id22734900800
person.identifier.scopus-author-id7004115775
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor
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relation.isAuthorOfPublication.latestForDiscoveryff1df02d-0c0f-4db1-bf7d-78863a99420b

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