A Fuzzy Approach for Similarity Measurement in Time Series, Case Study for Stocks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F20%3AA21025VN" target="_blank" >RIV/61988987:17610/20:A21025VN - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-50153-2_42" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-50153-2_42</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-50153-2_42" target="_blank" >10.1007/978-3-030-50153-2_42</a>
Alternative languages
Result language
angličtina
Original language name
A Fuzzy Approach for Similarity Measurement in Time Series, Case Study for Stocks
Original language description
In this paper, we tackle the issue of assessing similarity among time series under the assumption that a time series can be additively decomposed into a trend-cycle and an irregular fluctuation. It has been proved before that the former can be well estimated using the fuzzy transform. In the suggested method, first, we assign to each time series an adjoint one that consists of a sequence of trend-cycle of a time series estimated using fuzzy transform. Then we measure the distance between local trend-cycles. An experiment is conducted to demonstrate the advantages of the suggested method. This method is easy to calculate, well interpretable, and unlike standard euclidean distance, it is robust to outliers.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
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)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Information Processing and Management of Uncertainty in Knowledge-Based Systems
ISBN
978-3-030-50152-5
ISSN
1865-0929
e-ISSN
—
Number of pages
11
Pages from-to
567-577
Publisher name
Springer
Place of publication
Cham
Event location
Lisabon
Event date
Jun 15, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—