Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection

Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection

The fuzzy rule sets, which have been derived from the hybrid neural network model, called the O-EGART-PR-FIS, is an integration of the Adaptive Resonance Theory (ART) into Generalized Regression Neural Network (GRNN), display substantial redundancy and low interpretability that leads to time-consumi...

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Bibliographic Details
Main Authors: Yap K.S., Wong S.Y., Tiong S.K.
Other Authors: 24448864400
Format: Conference Paper
Published: 2023
Subjects:
Fault Detection
Fuzzy Inference System
Genetic Algorithm
Rule Extraction
Factory automation
Fault detection
Genetic algorithms
Neural networks
Adaptive resonance theory
Bench-mark problems
Classification performance
Fuzzy inference systems
Generalized Regression Neural Network(GRNN)
Hybrid neural networks
Prediction process
Rule extraction
Fuzzy rules
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