Change detection in streaming data analytics: a comparison of Bayesian online and martingale approaches

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dc.contributor.authorNamoano, Bernadin
dc.contributor.authorEmmanouilidis, Christos
dc.contributor.authorRuiz-Carcel, Cristobal
dc.contributor.authorStarr, Andrew G.
dc.date.accessioned2021-04-14T14:33:30Z
dc.date.available2021-04-14T14:33:30Z
dc.date.issued2020-12-18
dc.description.abstractOn line change detection is a key activity in streaming analytics, which aims to determine whether the current observation in a time series marks a change point in some important characteristic of the data, given the sequence of data observed so far. It can be a challenging task when monitoring complex systems, which are generating streaming data of significant volume and velocity. While applicable to diverse problem domains, it is highly relevant to monitoring high value and critical engineering assets. This paper presents an empirical evaluation of two algorithmic approaches for streaming data change detection. These are a modified martingale and a Bayesian online detection algorithm. Results obtained with both synthetic and real world data sets are presented and relevant advantages and limitations are discussed.en_UK
dc.identifier.citationNamoano B, Emmanouilidis C, Ruiz Carcel C, Starr A. (2020) Change detection in streaming data analytics: a comparison of Bayesian online and martingale approaches. IFAC-PapersOnLine, Volume 53, Issue 3, 2020, pp. 336-341en_UK
dc.identifier.issn2405-8963
dc.identifier.urihttps://doi.org/10.1016/j.ifacol.2020.11.054
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16571
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBayesian online detectionen_UK
dc.subjectmartingaleen_UK
dc.subjectchange detectionen_UK
dc.subjectstreaming analyticsen_UK
dc.titleChange detection in streaming data analytics: a comparison of Bayesian online and martingale approachesen_UK
dc.typeArticleen_UK

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