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Intuitionistic Fuzzy Neural Network: The Case of Credit Scoring Using Text Information

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F15%3A39899799" target="_blank" >RIV/00216275:25410/15:39899799 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-23983-5_31" target="_blank" >http://dx.doi.org/10.1007/978-3-319-23983-5_31</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-23983-5_31" target="_blank" >10.1007/978-3-319-23983-5_31</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Intuitionistic Fuzzy Neural Network: The Case of Credit Scoring Using Text Information

  • Original language description

    Intuitionistic fuzzy inference systems (IFISs) incorporate imprecision in the construction of membership functions present in fuzzy inference systems. In this paper we design intuitionistic fuzzy neural networks to adapt the antecedent and consequent parameters of IFISs. We also propose a mean of maximum defuzzification method for a class of Takagi-Sugeno IFISs and this method is compared with the center of area and basic defuzzification distribution operator. On credit scoring data, we show that the intuitionistic fuzzy neural network trained with gradient descent and Kalman filter algorithms outperforms the traditional ANFIS method.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA13-10331S" target="_blank" >GA13-10331S: The role of text information in corporate financial distress prediction models – country-specific and industry-specific approaches</a><br>

  • Continuities

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

Others

  • Publication year

    2015

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Engineering Applications of Neural Networks: 16th International Conference, EANN 2015

  • ISBN

    978-3-319-23981-1

  • ISSN

    1865-0929

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    337-346

  • Publisher name

    Springer

  • Place of publication

    Berlin

  • Event location

    Rhodes

  • Event date

    Sep 25, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article