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Interval-Valued Fuzzy Cognitive Maps with Genetic Learning for Predicting Corporate Financial Distress

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F18%3A39913375" target="_blank" >RIV/00216275:25410/18:39913375 - isvavai.cz</a>

  • Result on the web

    <a href="http://journal.pmf.ni.ac.rs/filomat/index.php/filomat/article/view/6669" target="_blank" >http://journal.pmf.ni.ac.rs/filomat/index.php/filomat/article/view/6669</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.2298/FIL1805657H" target="_blank" >10.2298/FIL1805657H</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Interval-Valued Fuzzy Cognitive Maps with Genetic Learning for Predicting Corporate Financial Distress

  • Original language description

    Fuzzy cognitive maps (FCMs) integrate neural networks and fuzzy logic to model complex nonlinear problems through causal reasoning. Interval-valued FCMs (IVFCMs) have recently been proposed to model additional uncertainty in decision-making tasks with complex causal relationships. In traditional FCMs, optimization algorithms are used to learn the strengths of the relationships from the data. Here, we propose a novel IVFCM with real-coded genetic learning. We demonstrate that the proposed method is effective for predicting corporate financial distress based on causally connected financial concepts. Specifically, we show that this method outperforms FCMs, fuzzy grey cognitive maps and adaptive neuro-fuzzy systems in terms of root mean squared error.

  • 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/GA16-19590S" target="_blank" >GA16-19590S: Topic and sentiment analysis of multiple textual sources for corporate financial decision-making</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Filomat

  • ISSN

    0354-5180

  • e-ISSN

  • Volume of the periodical

    32

  • Issue of the periodical within the volume

    5

  • Country of publishing house

    RS - THE REPUBLIC OF SERBIA

  • Number of pages

    6

  • Pages from-to

    1657-1662

  • UT code for WoS article

    000450221000017

  • EID of the result in the Scopus database

    2-s2.0-85061309227