All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Credit rating analysis using adaptive fuzzy rule-based systems: An industry-specific approach

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F12%3A39895048" target="_blank" >RIV/00216275:25410/12:39895048 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/s10100-011-0229-0" target="_blank" >http://dx.doi.org/10.1007/s10100-011-0229-0</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10100-011-0229-0" target="_blank" >10.1007/s10100-011-0229-0</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Credit rating analysis using adaptive fuzzy rule-based systems: An industry-specific approach

  • Original language description

    This paper presents an analysis of credit rating using fuzzy rule-based systems. The disadvantage of the models used in previous studies is that it is difficult to extract understandable knowledge from them. The root of this problem is the use of naturallanguage that is typical for the credit rating process. This problem can be solved using fuzzy logic, which enables users to model the meaning of natural language words. Therefore, the fuzzy rule-based system adapted by a feed-forward neural network isdesigned to classify US companies (divided into the finance, manufacturing, mining, retail trade, services, and transportation industries) and municipalities into the credit rating classes obtained from rating agencies. Features are selected using a filter combined with a genetic algorithm as a search method. The resulting subsets of features confirm the assumption that the rating process is industry-specific (i. e. specific determinants are used for each industry). The results show that

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GP402%2F09%2FP090" target="_blank" >GP402/09/P090: Modelling of Municipal Finance by Computational Intelligence Methods</a><br>

  • Continuities

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

Others

  • Publication year

    2012

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Central European Journal of Operations Research

  • ISSN

    1435-246X

  • e-ISSN

  • Volume of the periodical

    20

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    14

  • Pages from-to

    421-434

  • UT code for WoS article

  • EID of the result in the Scopus database