This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.
Transient stability analysis of electrical power systems using a neural network based on fuzzy ARTMAP
01.12.2003
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Synchronous machinery , Fuzzy set theory , Adaptive resonance theory , Electric energy systems , Fuzzy ARTMAP architecture , Synchronous machine , Standby power systems , Neural network , Power systems , Frequency stability , Transient analysis , Transient stability analysis , Fuzzy ARTMAP , Power quality , Neural networks , Quality control , Electrical power system
Application of Fuzzy ARTMAP Neural Network in TM Image Classification
British Library Online Contents | 2004
|Optoelectronic fuzzy ARTMAP processor
British Library Conference Proceedings | 1995
|NEURAL NETWORK MODEL BASED ON FUZZY ARTMAP FOR FORECASTING OF HIGHWAY TRAFFIC DATA
British Library Conference Proceedings | 2006
|Fuzzy ARTMAP Neural Network and Its Application to Fault Diagnosis of Integrated Navigation Systems
British Library Conference Proceedings | 1999
|Failure Diagnosis System Using ARTMAP Neural Networks
Online Contents | 1995
|