Design and tuning of fuzzy if-then rules for automatic classification

Design and tuning of fuzzy if-then rules for automatic classification

We propose an approach to the design and tuning of fuzzy rules for automatic classification decision making. This approach is based upon the finding of the weights of fuzzy if-then rules and the shapes of membership functions that minimize the difference between real (desired) and inferred (theoreti...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Rotshtein, A., Katelnikov, D.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Automatic control
Control systems
Decision making
Fuzzy logic
Fuzzy systems
Information management
Input variables
Medical control systems
Medical diagnostic imaging
Shape
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Beschreibung
Zusammenfassung:We propose an approach to the design and tuning of fuzzy rules for automatic classification decision making. This approach is based upon the finding of the weights of fuzzy if-then rules and the shapes of membership functions that minimize the difference between real (desired) and inferred (theoretical) classes of decisions. The problem of fuzzy model tuning is stated as a classical mathematical optimization problem.
DOI:10.1109/NAFIPS.1998.715528