@article {3067,
	title = {Smart Algorithm Based on the Optimization of SVR Technique by k-NNR Method for the Prognosis of the Open-Circuit and the Reversed Polarity Faults in a PV Generator, Decembre, ISSN/ISBN 1974-98211974-983X},
	journal = {IREMOS International Review on Modelling and Simulations.},
	volume = { Vol 8},
	number = {N{\textdegree}5},
	year = {2015},
	pages = {pp .18-25},
	abstract = {This paper deals with a new smart algorithm allowing open-circuit and reversed polarity faults prognosis in photovoltaic generators. Its contribution lies on the optimization of support vector regression (SVR) technique by a k-NN regression tool (k-NNR) for undetermined outputs. To testing the performance of the proposed algorithm, we used a significant data base containing the generator functioning history, and as indicators we selected variance, standard deviation, Confidence interval, absolute and relative errors. Nomenclature PV Photovoltaic SVM Support Vector Machines SVR Support Vector Regression k-NNR k-Nearest Neighbor Regression X SVR input vector Y SVR output vector f Linear function Ф Nonlinear mapping function w Weight vector e Squared loss function x Problem variable x * New problem variable α Lagrange multipliers N Number of classes m Number of index of minimum distances I / V Current / Voltage IPH Photocurrent},
	url = {https://hal.archives-ouvertes.fr/hal-01154195},
	author = {Rezgui Wail and Mouss Leila Hayet and Mouss Med Djamel}
}
