Robust prediction with ANNBFIS system

Authors:
Robert Czabanski;Michal Jezewski;Krzysztof Horoba;Janusz Jezewski;Janusz Wrobel
Affiliations:
Silesian University of Technology, Institute of Electronics, Gliwice, Poland;Silesian University of Technology, Institute of Electronics, Gliwice, Poland;Department of Biomedical Informatics, Institute of Medical Technology and Equipment, Zabrze, Poland;Department of Biomedical Informatics, Institute of Medical Technology and Equipment, Zabrze, Poland;Department of Biomedical Informatics, Institute of Medical Technology and Equipment, Zabrze, Poland
Venue:
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Year:
2010

Citing 3
Cited 1

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Robust extraction of fuzzy rules with artificial neural network based on fuzzy inference system

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Abstract

In this paper a learning method of Artificial Neural Network Based on Fuzzy Inference System (ANNBFIS) is presented. It is based on deterministic annealing, ε-insensitive learning by solving a system of linear inequalities, and robust fuzzy c-means clustering. To find the unknown number of fuzzy if-then rules we proposed the procedure of robust clusters merging. The performance of the learning method was demonstrated through the benchmark sunspot prediction problem.