Detection of structural breaks and perceptionally important points in time series

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F18%3AA1901UUN" target="_blank" >RIV/61988987:17610/18:A1901UUN - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Detection of structural breaks and perceptionally important points in time series
Original language description
In this paper we suggest to use special fuzzy modeling techniques for detection of structural breaks and perceptionally important points in time series, namely the fuzzy (F-)transform and one method of Fuzzy Natural Logic (FNL). The idea is based on application of the F^1-transform which makes it possible to estimate effectively slope of time series over an imprecisely specified area (ignoring its possible volatility) and its evaluation by a suitable evaluative linguistic expression. The method is computationally very effective.
Czech name
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Czech description
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Project
<a href="/en/project/GA18-13951S" target="_blank" >GA18-13951S: New approaches to financial time series modelling based on soft computing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Data Science and Knowledge Engineering for Sensing Decision Support
ISBN
978-981-3273-22-1
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1417-1424
Publisher name
World Scientific
Place of publication
New Jersey
Event location
Belfast
Event date
Aug 21, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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