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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • 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