@article{(Open Science Index):https://publications.waset.org/pdf/11210,
	  title     = {High Impedance Fault Detection using LVQ Neural Networks },
	  author    = {Abhishek Bansal and  G. N. Pillai},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response. },
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {1},
	  number    = {4},
	  year      = {2007},
	  pages     = {701 - 705},
	  ee        = {https://publications.waset.org/pdf/11210},
	  url   	= {https://publications.waset.org/vol/4},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 4, 2007},
	}