@article {1733,
	title = {Optimization of SVM Classifier by k-NN for the Smart Diagnosis of the Short-Circuit and Impedance Faults in a PV Generator, Decembre 2014, ISSN/ISBN: 1974-9821/1974-983X.},
	journal = {International Review on Modelling and Simulations(IREMOS)},
	volume = {07},
	number = {05},
	year = {2014},
	pages = {77-84. },
	abstract = {his paper deals with a new algorithm allowing short-circuit and impedance faults smart diagnosis of PV generators. It is based on the use of the SVM technique for the classification of observations not located in its margin, otherwise the proposed algorithm is used a k-NN method. A PV generator database containing observations distributed over classes is used for testing the new algorithm performance, which shows therefore its contribution and its effectiveness in the diagnosis area.Copyright {\textcopyright} 2014 Praise Worthy Prize - All rights reserved.},
	url = { https://doi.org/10.15866/iremos.v7i5.3442	},
	author = {Rezgui Wail and Mouss kinza Nadia and Mouss Med Djamel}
}
