Intuitionistic fuzzy neural network for time series forecasting - The case of metal prices
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F21%3A39917741" target="_blank" >RIV/00216275:25410/21:39917741 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-79150-6_33" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-79150-6_33</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-79150-6_33" target="_blank" >10.1007/978-3-030-79150-6_33</a>
Alternative languages
Result language
angličtina
Original language name
Intuitionistic fuzzy neural network for time series forecasting - The case of metal prices
Original language description
Forecasting time series is an important problem addressed for years. Despite that, it still raises an active interest of researchers. The main issue related to that problem is the inherent uncertainty in data which is hard to be represented in the form of a forecasting model. To solve that issue, a fuzzy model of time series was proposed. Recent developments of that model extend the level of uncertainty involved in data using intuitionistic fuzzy sets. It is, however, worth noting that additional fuzziness exhibits nonlinear behavior. To cope with that issue, we propose a time series model that represents both high uncertainty and non-linearity involved in the data. Specifically, we propose a forecasting model integrating intuitionistic fuzzy sets with neural networks for predicting metal prices. We validate our approach using five financial multivariate time series. The results are compared with those produced by state-of-the-art fuzzy time series models. Thus, we provide solid evidence of high effectiveness of our approach for both one- and five-day-ahead forecasting horizons.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IFIP Advances in Information and Communication Technology. Vol. 627
ISBN
978-3-030-79149-0
ISSN
1868-4238
e-ISSN
1868-422X
Number of pages
12
Pages from-to
411-422
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
ONLINE
Event date
Jun 25, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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