Zobrazeno 1 - 10
of 2 656
pro vyhledávání: '"Bouallegue A"'
Autor:
Lang, Simon, Alexe, Mihai, Chantry, Matthew, Dramsch, Jesper, Pinault, Florian, Raoult, Baudouin, Clare, Mariana C. A., Lessig, Christian, Maier-Gerber, Michael, Magnusson, Linus, Bouallègue, Zied Ben, Nemesio, Ana Prieto, Dueben, Peter D., Brown, Andrew, Pappenberger, Florian, Rabier, Florence
Machine learning-based weather forecasting models have quickly emerged as a promising methodology for accurate medium-range global weather forecasting. Here, we introduce the Artificial Intelligence Forecasting System (AIFS), a data driven forecast m
Externí odkaz:
http://arxiv.org/abs/2406.01465
Artificial intelligence (AI), based on deep-learning algorithm using high-quality reanalysis datasets, is showing enormous potential for weather forecasting. In this context, the European Centre for Medium-Range Weather Forecasts (ECMWF) is developin
Externí odkaz:
http://arxiv.org/abs/2405.02679
Autor:
Ben-Bouallegue, Zied
A new index for high-impact weather forecasting is introduced and assessed in comparison with the well-established extreme forecast index (EFI). Two other ensemble summary statistics are also included in this comparison study: the shift-of-tail and a
Externí odkaz:
http://arxiv.org/abs/2312.01673
Autor:
Ouahidi, Yassine El, Gripon, Vincent, Pasdeloup, Bastien, Bouallegue, Ghaith, Farrugia, Nicolas, Lioi, Giulia
We propose EEG-SimpleConv, a straightforward 1D convolutional neural network for Motor Imagery decoding in BCI. Our main motivation is to propose a simple and performing baseline to compare to, using only very standard ingredients from the literature
Externí odkaz:
http://arxiv.org/abs/2309.07159
Autor:
Rasp, Stephan, Hoyer, Stephan, Merose, Alexander, Langmore, Ian, Battaglia, Peter, Russel, Tyler, Sanchez-Gonzalez, Alvaro, Yang, Vivian, Carver, Rob, Agrawal, Shreya, Chantry, Matthew, Bouallegue, Zied Ben, Dueben, Peter, Bromberg, Carla, Sisk, Jared, Barrington, Luke, Bell, Aaron, Sha, Fei
WeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in data-driven weather modeling. WeatherBench 2 consists of an open-source e
Externí odkaz:
http://arxiv.org/abs/2308.15560
Autor:
Ben-Bouallegue, Zied, Clare, Mariana C A, Magnusson, Linus, Gascon, Estibaliz, Maier-Gerber, Michael, Janousek, Martin, Rodwell, Mark, Pinault, Florian, Dramsch, Jesper S, Lang, Simon T K, Raoult, Baudouin, Rabier, Florence, Chevallier, Matthieu, Sandu, Irina, Dueben, Peter, Chantry, Matthew, Pappenberger, Florian
Data-driven modeling based on machine learning (ML) is showing enormous potential for weather forecasting. Rapid progress has been made with impressive results for some applications. The uptake of ML methods could be a game-changer for the incrementa
Externí odkaz:
http://arxiv.org/abs/2307.10128
Publikováno v:
e-Prime: Advances in Electrical Engineering, Electronics and Energy, Vol 9, Iss , Pp 100741- (2024)
Vehicle-to-vehicle (V2V) communication is a promising solution for enhancing network performance. This paper presents the modeling and performance analysis of moving V2V fifth generation new radio (5G NR) systems using Poisson point process (PPP) and
Externí odkaz:
https://doaj.org/article/63c9dec9a2894bcda1d061ba3cedbbf6
Autor:
Ben-Bouallegue, Zied, Weyn, Jonathan A, Clare, Mariana C A, Dramsch, Jesper, Dueben, Peter, Chantry, Matthew
Statistical post-processing of global ensemble weather forecasts is revisited by leveraging recent developments in machine learning. Verification of past forecasts is exploited to learn systematic deficiencies of numerical weather predictions in orde
Externí odkaz:
http://arxiv.org/abs/2303.17195
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract The term “Internet of Things” (IoT) refers to a system of networked computing devices that may work and communicate with one another without direct human intervention. It is one of the most exciting areas of computing nowadays, with its
Externí odkaz:
https://doaj.org/article/50992f5461cc425baadff7083c601d1b
Publikováno v:
In e-Prime - Advances in Electrical Engineering, Electronics and Energy September 2024 9