IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/460916.html
   My bibliography  Save this article

Credit Rating Using Type-2 Fuzzy Neural Networks

Author

Listed:
  • Rahib H. Abiyev

Abstract

Nowadays various new technologies such as artificial neural networks, genetic algorithms, and decision trees are used for modelling of credit rating. This paper presents design of credit rating model using a type-2 fuzzy neural networks (FNN). In the paper, the structure of the type-2 FNN is designed and its learning algorithm is derived. The proposed network is constructed on the base of a set of fuzzy rules that includes type-2 fuzzy sets in the antecedent part and a linear function in the consequent part of the rules. A fuzzy clustering algorithm and gradient learning algorithm are implemented for generation of the rules and identification of parameters. Effectiveness of the proposed system is evaluated with the results obtained from the simulation of type-2 FNN based systems and with the comparative simulation results of previous related models.

Suggested Citation

  • Rahib H. Abiyev, 2014. "Credit Rating Using Type-2 Fuzzy Neural Networks," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-8, March.
    • Handle: RePEc:hin:jnlmpe:460916
    DOI: 10.1155/2014/460916
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2014/460916.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2014/460916.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2014/460916?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Srđan Jelinek & Pavle Milošević & Aleksandar Rakićević & Ana Poledica & Bratislav Petrović, 2022. "A Novel IBA-DE Hybrid Approach for Modeling Sovereign Credit Ratings," Mathematics, MDPI, vol. 10(15), pages 1-21, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:460916. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.