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Neural intuitionistic fuzzy system with justified granularity

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F22%3A39919466" target="_blank" >RIV/00216275:25410/22:39919466 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/article/10.1007/s00521-022-07504-x" target="_blank" >https://link.springer.com/article/10.1007/s00521-022-07504-x</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s00521-022-07504-x" target="_blank" >10.1007/s00521-022-07504-x</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Neural intuitionistic fuzzy system with justified granularity

  • Original language description

    Fuzzy systems are intensively investigated and extended to construct forecasting models. In particular, intuitionistic fuzzy sets are used to capture higher levels of uncertainty occurring in the modeled data. Neural networks are also used to reflect nonlinearity relationships frequently observed in time series. This paper proposes a new hybrid system merging fuzzy system with neural networks and an advanced optimization technique, the principle of justified granularity. Using this technique, we construct an innovative time-series forecasting model. In the experimental part of the paper, we demonstrate the advantages arising from applying the proposed approach to metal price forecasting. Finally, we provide evidence that the proposed model is competitive with the current state-of-the-art models for the forecasting horizons of one and five days.

  • 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

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Neural Computing and Applications

  • ISSN

    0941-0643

  • e-ISSN

    1433-3058

  • Volume of the periodical

    34

  • Issue of the periodical within the volume

    Neuveden

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    17

  • Pages from-to

    19423-19439

  • UT code for WoS article

    000820553800004

  • EID of the result in the Scopus database

    2-s2.0-85133455875