On designing of flexible neuro-fuzzy systems for classification

Authors:
Krzysztof Cpałka;Leszek Rutkowski
Affiliations:
Department of Computer Engineering, Czestochowa University of Technology, Poland;Department of Computer Engineering, Czestochowa University of Technology, Poland
Venue:
ISTASC'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Systems Theory and Scientific Computation - Volume 7
Year:
2007

Citing 11
Cited 0

On fuzzy implication operators

Fuzzy Sets and Systems
Essentials of fuzzy modeling and control

Essentials of fuzzy modeling and control
Neuro-fuzzy systems for function approximation

Fuzzy Sets and Systems - Special issue on analytical and structural considerations in fuzzy modeling
Computational intelligence systems and applications: neuro-fuzzy and fuzzy neural synergisms

Computational intelligence systems and applications: neuro-fuzzy and fuzzy neural synergisms
Foundations of Neuro-Fuzzy Systems

Foundations of Neuro-Fuzzy Systems
Soft Computing and Its Applications

Soft Computing and Its Applications
Flexible Neuro-fuzzy Systems: Structures, Learning and Performance Evaluation (Kluwer International Series in Engineering and Computer Science)

Flexible Neuro-fuzzy Systems: Structures, Learning and Performance Evaluation (Kluwer International Series in Engineering and Computer Science)
DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction

IEEE Transactions on Fuzzy Systems
Self-adaptive neuro-fuzzy inference systems for classification applications

IEEE Transactions on Fuzzy Systems
Designing and learning of adjustable quasi-triangular norms with applications to neuro-fuzzy systems

IEEE Transactions on Fuzzy Systems
Flexible neuro-fuzzy systems

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the paper we propose a new method for designing flexible neuro-fuzzy systems applied to classification. The systems are characterized by weighted triangular norms describing the importance of linguistic variables and rules. An algorithm for complexity reduction of such systems is developed and simulation results are presented.