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Title: Neural Network Training by Gradient Descent Algorithms: Application on Parametric Identification of Solar Cell

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Title:
Neural Network Training by Gradient Descent Algorithms: Application on Parametric Identification of Solar Cell
Author Name:
Fayrouz Dkhichi and Benyounes Oukarfi
Abstract:
This paper present the parametric identification of solar cell by using an artificial neural network trained at every time, separately, by one algorithm among the optimization algorithms of gradient descent (Levenberg-Marquardt, Gauss-Newton, Quasi-Newton, steepest descent and conjugate gradient). This determination issue is made for different values of temperature and irradiance. The training process is insured by the minimization of the error generated at the network output. Therefore, from the outcomes obtained by each gradient descent algorithm, we conducted a comparative study between the overall of training algorithms in order to know which one had the best performances. As a result the Levenberg-Marquardt algorithm presents the best potential compared to the other investigated optimization algorithms of gradient descent.
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