Fault detection and diagnosis using an art-based neural network
The Generalized Adaptive Resonance Theory (GART) network is a neural network model based on the integration of Gaussian ARTMAP and the Generalized Regression Neural Network. It is capable of online learning, and is effective in tackling classification as well as regression tasks, as demonstrated in...
Saved in:
Main Authors: | Yap K.S., Au M.T., Lim C.P., Saleh J.M. |
---|---|
Other Authors: | 24448864400 |
Format: | Conference paper |
Published: |
Acta Press
2023
|
Subjects: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An enhanced generalized adaptive resonance theory neural network and its application to medical pattern classification
by: Yap K.S., et al.
Published: (2023) -
Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection
by: Yap K.S., et al.
Published: (2023) -
Development and application of an enhanced ART-Based neural network
by: Keem, Siah Yap, et al.
Published: (2009) -
Improved GART neural network model for pattern classification and rule extraction with application to power systems
by: Yap K.S., et al.
Published: (2023) -
A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function
by: Yap K.S., et al.
Published: (2023)