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Online Recognition of Fuzzy Time Series Patterns

This article deals with the recognition of recurring
multivariate time series patterns modelled sample-point-wise by parametric
fuzzy sets. An efficient classification-based approach for the
online recognition of incompleted developing patterns in streaming
time series is being presented. Furthermore, means are introduced
to enable users of the recognition system to restrict results to certain
stages of a pattern’s development, e. g. for forecasting purposes, all
in a consistently fuzzy manner.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:19176
Date10 August 2009
CreatorsHerbst, Gernot
ContributorsBocklisch, Steffen F.
PublisherTechnische Universität Chemnitz
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text
SourceProceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference (IFSA-EUSFLAT 2009), Lisbon, Portugal, July 20-24, 2009.
Rightsinfo:eu-repo/semantics/openAccess
Relation978-989-95079-6-8

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