Time Series: How Unusual Local Behavior Can Be Recognized Using Fuzzy Modeling Methods

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F21%3AA2202DMF" target="_blank" >RIV/61988987:17610/21:A2202DMF - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-45619-1_13" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-45619-1_13</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-45619-1_13" target="_blank" >10.1007/978-3-030-45619-1_13</a>

Result language
angličtina
Original language name
Time Series: How Unusual Local Behavior Can Be Recognized Using Fuzzy Modeling Methods
Original language description
In this paper, we address the problem of automatic recognition of structural breaks in time series. The former are unexpected shifts of the course or sudden change of the volatility of time series. Structural breaks can be caused, e.g., by changes in the organization of a company, global or local economic development, global shifts in capital and labor, various kinds of outer influences such as discovery or depletion of natural resources, etc. Structural breaks in time series are usually detected using statistical methods. In this paper, we suggest using special non-statistical techniques of fuzzy modeling. We will employ two classes of them, namely the fuzzy transform and selected methods of Fuzzy Natural Logic. The fuzzy transform enables us to estimate the average slope of time series in an area characterized by a fuzzy set. The slope is then evaluated by evaluative linguistic expressions, which enables us to identify intervals with monotonous behavior and, consequently, identify structural breaks. Our method is simple, transparent, and computationally effective.
Czech name
—
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
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name
Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas
ISBN
978-3-030-45618-4
Number of pages of the result
21
Pages from-to
157-177
Number of pages of the book
265
Publisher name
Springer
Place of publication
Cham
UT code for WoS chapter
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