Title :
An adaptive fuzzy technique for learning power-quality signature waveforms
Author :
Ibrahim, W. R Anis ; Morcos, M.M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Kansas State Univ., Manhattan, KS, USA
fDate :
1/1/2001 12:00:00 AM
Abstract :
This letter presents a new technique for learning power-quality waveforms. The approach is an intelligent technique based on exploiting the capabilities of adaptive fuzzy logic learning. The development of the mechanism was essential for the completion of an intelligent fuzzy expert system targeting power-quality problems using a mal-operation prediction technique
Keywords :
expert systems; fuzzy logic; learning (artificial intelligence); power supply quality; power system analysis computing; adaptive fuzzy logic learning; adaptive fuzzy technique; intelligent fuzzy expert system; intelligent technique; mal-operation prediction technique; power-quality problems; power-quality signature waveforms learning; Adaptive systems; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Hybrid intelligent systems; Intelligent systems; Neural networks; Power quality; System testing;
Journal_Title :
Power Engineering Review, IEEE
