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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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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
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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
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