Mathematical optimization for time series decomposition
dc.contributor.author | Gözüyılmaz, Şeyma | |
dc.contributor.author | Kundakcıoğlu, Ömer Erhun | |
dc.date.accessioned | 2022-08-16T10:41:10Z | |
dc.date.available | 2022-08-16T10:41:10Z | |
dc.date.issued | 2021-09 | |
dc.identifier.issn | 0171-6468 | en_US |
dc.identifier.uri | http://hdl.handle.net/10679/7810 | |
dc.identifier.uri | https://link.springer.com/article/10.1007/s00291-021-00637-w | |
dc.description.abstract | Decomposing time series into trend and seasonality components reveals insights used in forecasting and anomaly detection. This study proposes a mathematical optimization approach that addresses several data-related issues in time series decomposition. Our approach does not only handle longer and multiple seasons but also identifies outliers and trend shifts. Numerical experiments on real-world and synthetic problem sets present the effectiveness of the proposed approach. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartof | OR Spectrum | |
dc.rights | restrictedAccess | |
dc.title | Mathematical optimization for time series decomposition | en_US |
dc.type | Article | en_US |
dc.peerreviewed | yes | en_US |
dc.publicationstatus | Published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0003-3033-0986 & YÖK ID 124068) Kundakcıoğlu, Erhun | |
dc.contributor.ozuauthor | Kundakcıoğlu, Ömer Erhun | |
dc.identifier.volume | 43 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.startpage | 733 | en_US |
dc.identifier.endpage | 758 | en_US |
dc.identifier.wos | WOS:000658605300001 | |
dc.identifier.doi | 10.1007/s00291-021-00637-w | en_US |
dc.subject.keywords | Time series | en_US |
dc.subject.keywords | Seasonal trend decomposition | en_US |
dc.subject.keywords | Mixed integer nonlinear programming | en_US |
dc.identifier.scopus | SCOPUS:2-s2.0-85107560254 | |
dc.contributor.ozugradstudent | Gözüyılmaz, Şeyma | |
dc.relation.publicationcategory | Article - International Refereed Journal - Institutional Academic Staff and Graduate Student |
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