dc.creator | Martínez Álvarez, Francisco | es |
dc.creator | Troncoso Lora, Alicia | es |
dc.creator | Riquelme Santos, José Cristóbal | es |
dc.creator | Aguilar Ruiz, Jesús Salvador | es |
dc.date.accessioned | 2016-07-08T08:18:40Z | |
dc.date.available | 2016-07-08T08:18:40Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Martínez Álvarez, F., Troncoso Lora, A., Riquelme Santos, J.C. y Aguilar Ruiz, J.S. (2011). Energy Time Series Forecasting Based on Pattern Sequence Similarity. IEEE Transactions on Knowledge and Data Engineering, 23 (8), 1230-1243. | |
dc.identifier.issn | 1041-4347 | es |
dc.identifier.uri | http://hdl.handle.net/11441/43385 | |
dc.description.abstract | This paper presents a new approach to forecast the behavior of time series based on similarity of pattern sequences. First,
clustering techniques are used with the aim of grouping and labeling the samples from a data set. Thus, the prediction of a data point is
provided as follows: first, the pattern sequence prior to the day to be predicted is extracted. Then, this sequence is searched in the
historical data and the prediction is calculated by averaging all the samples immediately after the matched sequence. The main novelty
is that only the labels associated with each pattern are considered to forecast the future behavior of the time series, avoiding the use of
real values of the time series until the last step of the prediction process. Results from several energy time series are reported and the
performance of the proposed method is compared to that of recently published techniques showing a remarkable improvement in the
prediction. | es |
dc.description.sponsorship | Ministerio de Ciencia y Tecnología TIN2007- 68084-C-00 | es |
dc.description.sponsorship | Junta de Andalucia P07-TIC- 02611 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | IEEE | es |
dc.relation.ispartof | IEEE Transactions on Knowledge and Data Engineering, 23 (8), 1230-1243. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Energy Time Series Forecasting Based on Pattern Sequence Similarity | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | TIN2007- 68084-C02-02 | es |
dc.relation.projectID | P07-TIC-02611 | es |
dc.identifier.doi | http://dx.doi.org/10.1109/TKDE.2010.227 | es |
idus.format.extent | 14 | es |
dc.journaltitle | IEEE Transactions on Knowledge and Data Engineering | es |
dc.publication.volumen | 23 | es |
dc.publication.issue | 8 | es |
dc.publication.initialPage | 1230 | es |
dc.publication.endPage | 1243 | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/43385 | |
dc.contributor.funder | Ministerio de Ciencia y Tecnología (MCYT). España | |
dc.contributor.funder | Junta de Andalucía | |