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.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa.de:bsz:ch1-200901287 |
| Date | 10 August 2009 |
| Creators | Herbst, Gernot |
| Contributors | TU Chemnitz, Fakultät für Elektrotechnik und Informationstechnik |
| Publisher | Universitätsbibliothek Chemnitz |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:conferenceObject |
| Format | application/pdf, text/plain, application/zip |
| Source | Proceedings 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. |
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