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- W2032935302 abstract "The present work documents the study on the usage of Neural Networks to compute the parameters used in solar panel modelling. The approach followed starts from a dataset obtained by a process of model identification via numerical solution of nonlinear equations. After a preliminary analysis pointing out the intrinsic difficulty in the classic identification of the parameters via NN, by taking advantage of closed form relations, a hybrid neural system, composed by neural network based identifiers and explicit equations, was implemented. The generalization capabilities of the neural identifier were investigated, showing the effectiveness of this approach." @default.
- W2032935302 created "2016-06-24" @default.
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- W2032935302 date "2014-01-01" @default.
- W2032935302 modified "2023-09-26" @default.
- W2032935302 title "Model Identification for Photovoltaic Panels Using Neural Networks" @default.
- W2032935302 doi "https://doi.org/10.5220/0005039201300137" @default.
- W2032935302 hasPublicationYear "2014" @default.
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