Publications associées à Spatio-temporal estimation of wind speed and wind power using extreme learning machines: predictions, uncertainty and technical potential

Publications associées (9)

Improving the accuracy and interpretability of neural networks for wind power forecasting

Fernando Porté Agel, Jiannong Fang, Wenlong Liao

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

2025

Probabilistic Load-Shedding Strategy for Frequency Regulation in Microgrids Under Uncertainties

Rafael Silva Alipio

This paper proposes a novel integer-mixed probabilistic optimal power flow (IM-POPF) strategy for frequency regulation in islanded microgrids under uncertain operating conditions. Existing load-shedding approaches face critical limitations: continuous fram ...

MDPI AG2025

Study of the decay (Formula presented)

Yunxuan Song

Using (Formula presented) (Formula presented) events collected with the BESIII detector operating at the BEPCII collider, we have observed the decay (Formula presented) for the first time with a statistical significance of (Formula presented). Its branchin ...

2025

What can radars tell us about snowfall microphysics? Insights from a Markov chain Monte-Carlo approach

Alexis Berne, Anne-Claire Marie Billault--Roux

Multi-frequency and Doppler spectral radars are valuable tools for retrieving information on the microphysics of precipitation, particularly snowfall. However, estimating microphysical properties from radar measurements is an ill-posed problem, i.e., diffe ...

American Meteorological Society2025

Influence of wind direction on flow over a cliff and its interaction with a wind turbine wake

Fernando Porté Agel, Arslan Salim Dar

2024

The complexity of quantum support vector machines

Gian Florin Gentinetta

Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets. The training of such models c ...

Verein Forderung Open Access Publizierens Quantenwissenschaf2024

Wake meandering of wind turbines under dynamic yaw control and impacts on power and fatigue

Fernando Porté Agel, Mou Lin

The wind turbine array consists of eight NREL 5-MW reference turbines aligned with the inflow direction. The first turbine in the array is subjected to sinusoidal yaw control with a magnitude of 10∘ and different yaw frequencies. Based on spectral and dyna ...

Pergamon-Elsevier Science Ltd2024

Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression

Lenka Zdeborová, Florent Gérard Krzakala, Bruno Loureiro, Adrien Vandenbroucque, Lucas Andry Clarte, Guillaume Cyprien Dalle

We investigate popular resampling methods for estimating the uncertainty of statistical models, such as subsampling, bootstrap and the jackknife, and their performance in high-dimensional supervised regression tasks. We provide a tight asymptotic descripti ...

ACM2024

Lattice Models and Conformal Field Theory

Clément Hongler, Franck Raymond Gabriel, Francesco Spadaro

This book introduces the mathematical ideas connecting Statistical Mechanics and Conformal Field Theory (CFT). Building advanced structures on top of more elementary ones, the authors map out a well-posed road from simple lattice models to CFTs. Structure ...

Courant Institute of Mathematical Sciences2024