Anomaly Detection Based on Principle of Justifiable Granularity and Probability Density Estimation

Basit Öğe Kaydı
dc.contributor.authorDu, S.
dc.contributor.authorMa, X.
dc.contributor.authorLi, X.
dc.contributor.authorWu, M.
dc.contributor.authorCao, W.
dc.contributor.authorPedrycz, W.
dc.date.accessioned2024-05-19T14:33:19Z
dc.date.available2024-05-19T14:33:19Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description2023 China Automation Congress, CAC 2023 -- 17 November 2023 through 19 November 2023 -- -- 198194en_US
dc.description.abstractAnomaly detection is essential to ensure the safety of industrial processes. This paper presents an anomaly detection approach based on the probability density estimation and principle of justifiable granularity. First, time series data are transformed into a two-dimensional information granule by the principle of justifiable granularity. Then, the test statistic is constructed, and the probability density and cumulative distribution functions of the test statistic are calculated. Next, the confidence level determines the test threshold. Finally, the time series data of a key parameter in the sintering process is used as a case study. The experimental result demonstrates that the proposed approach can detect abnormal time series data effectively, providing an accurate and effective solution for detecting time series anomalies in industrial processes. © 2023 IEEE.en_US
dc.identifier.doi10.1109/CAC59555.2023.10450590
dc.identifier.endpage1367en_US
dc.identifier.isbn9798350303759
dc.identifier.scopus2-s2.0-85189315921en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1364en_US
dc.identifier.urihttps://doi.org/10.1109/CAC59555.2023.10450590
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4186
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 2023 China Automation Congress, CAC 2023en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectAnomaly Detectionen_US
dc.subjectPrinciple Of Justifiable Granularityen_US
dc.subjectProbability Density Estimationen_US
dc.subjectTime Seriesen_US
dc.titleAnomaly Detection Based on Principle of Justifiable Granularity and Probability Density Estimationen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu