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Communication Dans Un Congrès Année : 2014

A Regression Algorithm for the Smart Prognosis of a Reversed Polarity Fault in a Photovoltaic Generator

Résumé

This paper deals with a smart algorithm allowing reversed polarity fault diagnosis and prognosis in PV generators. The proposed prognosis (prediction) approach is based on the hybridization of a support vector regression (SVR) technique optimized by a k-NN regression tool (K-NNR) for undetermined outputs. To test the proposed algorithm performance, a PV generator database containing sample data is used for simulation purposes.
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Dates et versions

hal-01023493 , version 1 (13-07-2014)

Identifiants

  • HAL Id : hal-01023493 , version 1

Citer

Wail Rezgui, Nadia Kinza Mouss, Leïla-Hayet Mouss, Mohamed Djamel Mouss, Mohamed Benbouzid. A Regression Algorithm for the Smart Prognosis of a Reversed Polarity Fault in a Photovoltaic Generator. IEEE ICGE 2014, Mar 2014, Sfax, Tunisia. pp.134-138. ⟨hal-01023493⟩
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