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Short-term load forecasting using radial basis function networks

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dc.contributor.author Gontar, Z en
dc.contributor.author Sideratos, G en
dc.contributor.author Hatziargyriou, N en
dc.date.accessioned 2014-03-01T02:42:58Z
dc.date.available 2014-03-01T02:42:58Z
dc.date.issued 2004 en
dc.identifier.issn 0302-9743 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/31158
dc.subject Liberalized Electricity Market en
dc.subject Radial Basis Function Network en
dc.subject Short Term Load Forecasting en
dc.subject.classification Computer Science, Theory & Methods en
dc.subject.other Cost benefit analysis en
dc.subject.other Economics en
dc.subject.other Electric load management en
dc.subject.other Energy management en
dc.subject.other Error analysis en
dc.subject.other Learning algorithms en
dc.subject.other Safety factor en
dc.subject.other Security systems en
dc.subject.other Energy exchanges en
dc.subject.other Learning procedure en
dc.subject.other Non-linear functions en
dc.subject.other Short-term load forecasting en
dc.subject.other Radial basis function networks en
dc.title Short-term load forecasting using radial basis function networks en
heal.type conferenceItem en
heal.identifier.primary 10.1007/978-3-540-24674-9_45 en
heal.identifier.secondary http://dx.doi.org/10.1007/978-3-540-24674-9_45 en
heal.language English en
heal.publicationDate 2004 en
heal.abstract This paper presents results from the application of Radial Basis Function Networks (RBFNs) to Short-Term Load Forecasting. Short-term Load Forecasting is nowadays a crucial function, especially in the operation of liberalized electricity markets, as it affects the economy and security of the system. Actual load series from Crete are used for the evaluation of the developed structures providing results of satisfactory accuracy, retaining the advantages of RBFNs. en
heal.publisher SPRINGER-VERLAG BERLIN en
heal.journalName Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) en
heal.bookName LECTURE NOTES IN COMPUTER SCIENCE en
dc.identifier.doi 10.1007/978-3-540-24674-9_45 en
dc.identifier.isi ISI:000221610800045 en
dc.identifier.volume 3025 en
dc.identifier.spage 432 en
dc.identifier.epage 438 en


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