Description: In this paper, the expert system is introduced in
order to detect and classify commonly power quality
disturbances. This system is using learning vector quantization
artificial neural networks. Clustering method named fuzzy
c-mean is also utilized to initialize weight vector of first hidden
layer. It can mitigate the disadvantage of LVQ ANN. The
proposed system employs wavelet decomposition coefficients for
extracting of deviated signals features. The determined feature
vector is derived from Standard Deviation of 10-level
decomposition detail coefficients. For the purpose of having
efficient network, just 3 characteristic points among 10 points
have been used, that leads to make networks training much
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File list (Check if you may need any files):
M_FILE\dcoffset.m
......\flicker.m
......\harmonic.m
......\impulsive.m
......\interruption.m
......\main3.m
......\noise.m
......\sag.m
......\swell.m
......\ten_level_std_detail.m
M_FILE
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