Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Sutera, Antonio"'
The energy transition is expected to significantly increase the share of renewable energy sources whose production is intermittent in the electricity mix. Apart from key benefits, this development has the major drawback of generating a mismatch betwe
Externí odkaz:
http://arxiv.org/abs/2301.11587
Publikováno v:
35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia
Random forests have been widely used for their ability to provide so-called importance measures, which give insight at a global (per dataset) level on the relevance of input variables to predict a certain output. On the other hand, methods based on S
Externí odkaz:
http://arxiv.org/abs/2111.02218
Autor:
Sutera, Antonio
Nowadays new technologies, and especially artificial intelligence, are more and more established in our society. Big data analysis and machine learning, two sub-fields of artificial intelligence, are at the core of many recent breakthroughs in many a
Externí odkaz:
http://arxiv.org/abs/2106.09473
Greater direct electrification of end-use sectors with a higher share of renewables is one of the pillars to power a carbon-neutral society by 2050. However, in contrast to conventional power plants, renewable energy is subject to uncertainty raising
Externí odkaz:
http://arxiv.org/abs/2106.09370
Autor:
Dumas, Jonathan, Cointe, Colin, Wehenkel, Antoine, Sutera, Antonio, Fettweis, Xavier, Cornélusse, Bertrand
This paper addresses the energy management of a grid-connected renewable generation plant coupled with a battery energy storage device in the capacity firming market, designed to promote renewable power generation facilities in small non-interconnect
Externí odkaz:
http://arxiv.org/abs/2105.13801
Dealing with datasets of very high dimension is a major challenge in machine learning. In this paper, we consider the problem of feature selection in applications where the memory is not large enough to contain all features. In this setting, we propo
Externí odkaz:
http://arxiv.org/abs/1709.01177
Publikováno v:
In Applied Energy 1 January 2022 305
In many cases, feature selection is often more complicated than identifying a single subset of input variables that would together explain the output. There may be interactions that depend on contextual information, i.e., variables that reveal to be
Externí odkaz:
http://arxiv.org/abs/1605.03848
Publikováno v:
In Electric Power Systems Research December 2020 189
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.