Multivariate spatial condition mapping using subtractive fuzzy cluster means

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aut.relation.endpage18981
aut.relation.issue10en_NZ
aut.relation.startpage18960
aut.relation.volume14en_NZ
aut.researcherAl-Anbuky, Adnan
dc.contributor.authorSabit, Hen_NZ
dc.contributor.authorAl-Anbuky, Aen_NZ
dc.date.accessioned2016-01-22T01:09:23Z
dc.date.available2016-01-22T01:09:23Z
dc.date.copyright2014-10-13en_NZ
dc.date.issued2014-10-13en_NZ
dc.description.abstractWireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining.en_NZ
dc.identifier.citationSensors 2014, 14(10), 18960-18981; doi:10.3390/s141018960en_NZ
dc.identifier.doi10.3390/s141018960en_NZ
dc.identifier.issn1424-8220en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/9390
dc.languageengen_NZ
dc.publisherMDPI AGen_NZ
dc.relation.urihttp://dx.doi.org/10.3390/s141018960
dc.rightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectData stream miningen_NZ
dc.subjectFuzzy clusteringen_NZ
dc.subjectSensor clouden_NZ
dc.subjectWireless sensor networken_NZ
dc.titleMultivariate spatial condition mapping using subtractive fuzzy cluster meansen_NZ
dc.typeJournal Article
pubs.elements-id173685
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/School of Engineering
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