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Credit Rating Using Type-2 Fuzzy Neural Networks. (Abiyev, Rahib H.,)
Bibliographical information (record 263959)
Credit Rating Using Type-2 Fuzzy Neural Networks.
Abiyev, Rahib H., Search Author in Amazon Books

Hindawi Publishing Corporation.
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    - Rahib H. Abiyev, “Credit Rating Using Type-2 Fuzzy Neural Networks,” Mathematical Problems in Engineering, vol. 2014, Article ID 460916, 8 pages, 2014. doi:10.1155/2014/460916
    - 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. [ABSTRACT FROM AUTHOR] . Copyright of Mathematical Problems in Engineering is the property of Hindawi Publishing Corporation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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NEU Grand LibraryOnline (TK5101 .C74 2014)
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