A new optimal feature selection algorithm for classification of power quality disturbances using discrete wavelet transform and probabilistic neural network

•Power quality disturbances are classified using optimal feature selection method.•Discrete wavelet transform extracts the set of features successfully.•Artificial bee colony has been proposed for the selection of optimal features.•16 types of single and multiple power quality disturbances are class...

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Veröffentlicht in:	Measurement : journal of the International Measurement Confederation 2017-01, Vol.95, p.246-259
Hauptverfasser:	Khokhar, Suhail, Mohd Zin, Abdullah Asuhaimi, Memon, Aslam Pervez, Mokhtar, Ahmad Safawi
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial bee colony Classification Classifiers Computer simulation Discrete Wavelet Transform Disturbances Feature extraction Neural networks Optimal feature selection Power quality disturbances Probabilistic neural network Rhythm Sensitivity analysis Swarm intelligence Wavelet transforms
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