Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8389
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dc.contributor.authorSingha, Yashwant-
dc.contributor.authorChugh b, Urvashi-
dc.contributor.authorMurthyC, Ramana-
dc.date.accessioned2022-11-29T10:52:19Z-
dc.date.available2022-11-29T10:52:19Z-
dc.date.issued2015-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8389-
dc.description.abstractuseful information i.e. Information Fusion. Information Fusion is sometime targeted for change point detection or it can be said for event detection in present scenario. This paper will present information fusion and change point detection merged with our previously proposed work i.e. Mutual Exclusive Distributive Clustering (MEDC). In this paper change point Detection is aimed for forest fire detection via fuzzy logic. MEDC protocol will perform clustering and after that, these cluster heads will use fuzzy logic to represent change point detection. Fire detection is considered here as application for change point detection. In this paper for simulation purpose, data is taken from National Oceanic and Atmospheric Administration [15] and Occupational Safety and health administrationen_US
dc.language.isoenen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectChange point detectionen_US
dc.subjectFuzzy theoryen_US
dc.subjectMEDCen_US
dc.titleInformation Fusion and Change Point Detection in Mutual Exclusive Distributive Clusteringen_US
dc.typeArticleen_US
Appears in Collections:Journal Articles

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