Antonio Ficarella

TL;DR: In this article, the authors compared various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction.

TL;DR: In this article, several forecast systems based on Artificial Neural Networks have been developed to predict power production of a wind farm located in a complex terrain, where geographical effects make wind speed predictions difficult.

TL;DR: In this article, different hybrid forecasting methods were applied to wind power prediction, using historical data and numerical weather predictions (NWP), and a comparative study was carried out for the prediction of the power production of a wind farm located in complex terrain, where the performances of Least Squares Support Vector Machine (LS-SVM) with Wavelet Decomposition (WD) were evaluated at different time horizons and compared to hybrid Artificial Neural Network (ANN)-based methods.

TL;DR: In this article, the authors compared the performance of battery-based and fuel-cell-based powertrains for low-energy UAVs with the same aircraft powered by different kinds of Lithium batteries sized to match the energy stored in the hydrogen tank.

TL;DR: In this paper, a numerical investigation is performed to analyse the suppression of boundary layer separation first on a NACA 0015 airfoil and subsequently in a highly loaded subsonic compressor stator cascade using two different active flow control techniques: synthetic jet actuators (SJA) and continuous jet actuator (CJA).