Municipal Creditworthiness Modelling by Kohonen's Self-Organizing Feature Maps and Fuzzy Logic Neural Networks

Authors:
Petr Hajek;Vladimir Olej
Affiliations:
Institute of System Engineering and Informatics Faculty of Economics and Administration, University of Pardubice, Pardubice, Czech Republic 53210;Institute of System Engineering and Informatics Faculty of Economics and Administration, University of Pardubice, Pardubice, Czech Republic 53210
Venue:
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Year:
2008

Citing 6
Cited 2

Hybrid neural nets can be fuzzy controllers and fuzzy expert systems

Fuzzy Sets and Systems
A neuro-fuzzy method to learn fuzzy classification rules from data

Fuzzy Sets and Systems - Special issue: application of neuro-fuzzy systems
Self-organizing maps

Self-organizing maps
Neural Networks: A Comprehensive Foundation

Neural Networks: A Comprehensive Foundation
Visual Explorations in Finance

Visual Explorations in Finance
Credit rating analysis with support vector machines and neural networks: a market comparative study

Decision Support Systems - Special issue: Data mining for financial decision making

Municipal Creditworthiness Modelling by Radial Basis Function Neural Networks and Sensitive Analysis of Their Input Parameters

ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Municipal credit rating modelling by neural networks

Decision Support Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper presents the design of municipal creditworthiness parameters. Further, the design of model for municipal creditworthiness classification is presented. The model is composed of Kohonen's self-organizing feature maps and fuzzy logic neural networks, where the output of Kohonen's self-organizing feature maps represents the input of fuzzy logic neural networks. It is a feed-forward fuzzy logic neural network with three layers. Standard neurons are replaced by fuzzy neurons in the fuzzy logic neural network.