Hybrid regrouping PSO based wavelet neural networks for characterization of acoustic signals due to surface discharges on H.V. glass insulators

Applied Soft Computing Journal

Volumn 13, Issue 12, 2013, Pages 4622-4632

  Al Geelani, Nasir A ^a   Piah, M Afendi M ^a   Adzis, Zuraimy ^a   Algeelani, Munir A ^b  

^a FACULTY OF ELECTRICAL ENGINEERING   (Malaysia)

^b UNIVERSITY OF ADEN   (Yemen)

Author keywords

Acoustic signal; Dry bands; Glass insulator; PSO and RegPSO; RBF NN; Surface discharge and wavelet transform

Indexed keywords

ACOUSTIC SIGNALS; DRY BAND; GLASS INSULATORS; PSO AND REGPSO; RBF-NN;

ACOUSTIC WAVES; ALGORITHMS; CLASSIFICATION (OF INFORMATION); ELECTRIC BREAKDOWN; GLASS; NEURAL NETWORKS; PARTICLE SWARM OPTIMIZATION (PSO); RADIAL BASIS FUNCTION NETWORKS; TESTING;

SURFACE DISCHARGES;

EID: 84886727964     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2013.07.011     Document Type: Article

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