Time series anomaly detection via rectangular information granulation for sintering process

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dc.authorscopusidWitold Pedrycz / 58861905800
dc.authorwosidWitold Pedrycz / HJZ-2779-2023
dc.contributor.authorDu, Sheng
dc.contributor.authorMa, Xian
dc.contributor.authorWu, Min
dc.contributor.authorCao, Weihua
dc.contributor.authorPedrycz, Witold
dc.date.accessioned2025-04-18T08:56:17Z
dc.date.available2025-04-18T08:56:17Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractTime series anomaly in the sintering process is a direct manifestation of equipment failure and abnormal operating mode, and effective detection of time series anomaly is important to improve the stability of the sintering process. This article presents a time series anomaly detection via rectangular information granulation, whose originality is to apply the similarity of information granules as a reference for anomaly detection. It converts time series into rectangular granules, and the similarity of time series is measured with rectangular granules. The one-way analysis of variance method is used to detect the difference for the similarity between the time series to be detected and the historical time series and the similarity between any two historical time series, thus achieving the anomaly detection of the time series. The experiment is conducted on real-world data from an enterprise. The result shows that the proposed method outperforms the probability density analysis method and can effectively detect abnormal time series.
dc.identifier.citationDu, S., Ma, X., Wu, M., Cao, W., & Pedrycz, W. (2024). Time Series Anomaly Detection Via Rectangular Information Granulation for Sintering Process. IEEE Transactions on Fuzzy Systems.
dc.identifier.doi10.1109/TFUZZ.2024.3404853
dc.identifier.endpage4804
dc.identifier.issn10636706
dc.identifier.issue8
dc.identifier.scopus2-s2.0-85194063952
dc.identifier.scopusqualityQ1
dc.identifier.startpage4799
dc.identifier.urihttp://dx.doi.org/10.1109/TFUZZ.2024.3404853
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6645
dc.identifier.volume32
dc.identifier.wosWOS:001291157800022
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorPedrycz, Witold
dc.institutionauthoridWitold Pedrycz / 0000-0002-9335-9930
dc.language.isoen
dc.publisherInstitute of electrical and electronics engineers inc.
dc.relation.ispartofIEEE transactions on fuzzy systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAnomaly Detection
dc.subjectRectangular Information Granulation
dc.subjectSintering Process
dc.subjectTime Series
dc.titleTime series anomaly detection via rectangular information granulation for sintering process
dc.typeArticle

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