SCOLS-FuM: A Hybrid Fuzzy Modeling Method for Telecommunications Time-Series Forecasting

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dc.contributor.author Mastorocostas, Paris A.
dc.contributor.author Hilas, Constantinos S.
dc.date.accessioned 2015-06-22T10:21:49Z
dc.date.available 2015-06-22T10:21:49Z
dc.date.issued 2014
dc.identifier.other http://www.mii.lt/Informatica/pdf/INFO894.pdf el
dc.identifier.uri http://apothesis.teicm.gr/xmlui/handle/123456789/1427
dc.description.abstract An application of fuzzy modeling to the problem of telecommunications time-series prediction is proposed in this paper. The model building process is a two-stage sequential algorithm, based on Subtractive Clustering (SC) and the Orthogonal Least Squares (OLS) techniques. Particularly, the SC is first employed to partition the input space and determine the number of fuzzy rules and the premise parameters. In the sequel, an orthogonal estimator determines the input terms which should be included in the consequent part of each fuzzy rule and calculate their parameters. A comparative analysis with well-established forecasting models is conducted on real world telecommunications data, where the characteristics of the proposed forecaster are highlighted. en
dc.format.extent 19 el
dc.language.iso en el
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.title SCOLS-FuM: A Hybrid Fuzzy Modeling Method for Telecommunications Time-Series Forecasting en
dc.type Άρθρο σε επιστημονικό περιοδικό el
dc.identifier.doi 10.15388/Informatica
dc.publication.category Δημοσίευση ανοιχτής πρόσβασης el
dc.relation.journal Informatica;
dc.subject.keyword Telecommunications data forecasting el
dc.subject.keyword Fuzzy modeling el
dc.subject.keyword Subtractive clustering el
dc.subject.keyword Orthogonal least squares el


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Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές