Intuitionistic fuzzy grey cognitive maps for forecasting interval-valued time series
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F20%3A39916135" target="_blank" >RIV/00216275:25410/20:39916135 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0925231220303489" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0925231220303489</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.neucom.2020.03.013" target="_blank" >10.1016/j.neucom.2020.03.013</a>
Alternative languages
Result language
angličtina
Original language name
Intuitionistic fuzzy grey cognitive maps for forecasting interval-valued time series
Original language description
In many real-world forecasting problems, the time series under investigation can be approximated. In that case, instead of dealing with its exact values, only their minima and maxima achieved in the predefined periods are considered. Such an approximation forms interval-valued time series (ITS). To forecast ITS, we propose a new method that relies on fuzzy cognitive maps (FCMs). We adapt standard FCMs to the forecasting of ITS using interval-valued intuitionistic fuzzy sets. In this way, we develop a forecasting model called the Intuitionistic Fuzzy Grey Cognitive Map (IFGCM). We validate our IFGCM using publicly available stock market data for 10 indexes for which the estimation of potential investment losses (minima) and gains (maxima) is crucial. The results of these experiments prove the high efficiency of the IFGCM, especially compared with state-of-the-art models.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA19-15498S" target="_blank" >GA19-15498S: Modelling emotions in verbal and nonverbal managerial communication to predict corporate financial risk</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neurocomputing
ISSN
0925-2312
e-ISSN
—
Volume of the periodical
400
Issue of the periodical within the volume
August
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
13
Pages from-to
173-185
UT code for WoS article
000544724700014
EID of the result in the Scopus database
2-s2.0-85081961194