273 citations · 358 across the 8 of their papers we have counts for
11 papers
Short-term solar irradiance and irradiation forecasts via different time series techniques: A preliminary study
Cédric Join, Cyril Voyant, Michel Fliess +4
This communication is devoted to solar irradiance and irradiation short-term forecasts, which are useful for electricity production. Several different time series approaches are em…
Meteorological time series forecasting with pruned multi-layer perceptron and 2-stage Levenberg-Marquardt method
Cyril Voyant, Wani W. Tamas, Marie Laure Nivet +4
A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its "black box" aspect, many researchers refuse…
Numerical weather prediction or stochastic modeling: an objective criterion of choice for the global radiation forecasting
Cyril Voyant, Gilles Notton, Christophe Paoli +3
Numerous methods exist and were developed for global radiation forecasting. The two most popular types are the numerical weather predictions (NWP) and the predictions using stochas…
Time series modeling and large scale global solar radiation forecasting from geostationary satellites data
Cyril Voyant, Pierrick Haurant, Marc Muselli +2
When a territory is poorly instrumented, geostationary satellites data can be useful to predict global solar radiation. In this paper, we use geostationary satellites data to gener…
Bayesian rules and stochastic models for high accuracy prediction of solar radiation
Cyril Voyant, C. Darras, Marc Muselli +3
It is essential to find solar predictive methods to massively insert renewable energies on the electrical distribution grid. The goal of this study is to find the best methodology…
Time series modeling with pruned multi-layer perceptron and 2-stage damped least-squares method
Cyril Voyant, Wani W. Tamas, Christophe Paoli +4
A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its "black box" aspect, many researchers refuse…