M
Marie Laure Nivet
Researcher at University of Corsica Pascal Paoli
Publications - 63
Citations - 3252
Marie Laure Nivet is an academic researcher from University of Corsica Pascal Paoli. The author has contributed to research in topics: Multilayer perceptron & Artificial neural network. The author has an hindex of 22, co-authored 63 publications receiving 2435 citations. Previous affiliations of Marie Laure Nivet include Centre national de la recherche scientifique & Society of Petroleum Engineers.
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Journal ArticleDOI
Machine learning methods for solar radiation forecasting: A review
Cyril Voyant,Gilles Notton,Soteris A. Kalogirou,Marie Laure Nivet,Christophe Paoli,Christophe Paoli,Fabrice Motte,Alexis Fouilloy +7 more
TL;DR: An overview of forecasting methods of solar irradiation using machine learning approaches is given and it will be shown that other methods begin to be used in this context of prediction.
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Forecasting of preprocessed daily solar radiation time series using neural networks
TL;DR: The optimized MLP presents predictions similar to or even better than conventional and reference methods such as ARIMA techniques, Bayesian inference, Markov chains and k-Nearest-Neighbors, as well as six prediction methods allow to predict the best daily DC PV power production at horizon d.
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Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting
Gilles Notton,Marie Laure Nivet,Cyril Voyant,Christophe Paoli,Christophe Darras,Fabrice Motte,Alexis Fouilloy +6 more
TL;DR: In this paper, the authors synthesize the reasons to predict solar or wind fluctuations, it shows that variability and stochastic variation of renewable sources have a cost, sometimes high, and provides useful information on the intermittence cost and on the decreasing of this cost due to an efficient forecasting of the source fluctuation.
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Numerical weather prediction (NWP) and hybrid ARMA/ANN model to predict global radiation
TL;DR: An original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (NWP) and the multi-layer perceptron (MLP) is proposed.
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Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation
TL;DR: In this paper, an application of Artificial Neural Networks (ANNs) to predict daily solar radiation on a horizontal surface was presented, where the use of exogenous data generated an nRMSE decrease between 0.5% and 1% for two stations during 2006 and 2007.