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An adaptive fuzzy technique for learning power-quality signature waveforms

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2 Author(s)
W. R. Anis Ibrahim ; Dept. of Electr. & Comput. Eng., Kansas State Univ., Manhattan, KS, USA ; M. M. Morcos

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

Published in:

IEEE Power Engineering Review  (Volume:21 ,  Issue: 1 )