Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Margaux Brégère"'
Autor:
Malo Huard, Margaux Brégère
Publikováno v:
International Journal of Forecasting
International Journal of Forecasting, 2022, 38 (1), pp.339-351. ⟨10.1016/j.ijforecast.2021.05.011⟩
International Journal of Forecasting, 2022, 38 (1), pp.339-351. ⟨10.1016/j.ijforecast.2021.05.011⟩
We study the forecasting of the power consumptions of a population of households and of subpopulations thereof. These subpopulations are built according to location, to exogenous information and/or to profiles we determined from historical households
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b366608cf684046458e855be34da9115
https://doi.org/10.1016/j.ijforecast.2021.05.011
https://doi.org/10.1016/j.ijforecast.2021.05.011
Autor:
Laure Sansonnet, Marie Perrot-Dockès, Céline Lévy-Leduc, Stéphane Robin, Grégory Genta-Jouve, Julien Chiquet, Margaux Brégère, Marie-Pierre Etienne
Publikováno v:
Statistical Applications in Genetics and Molecular Biology
Statistical Applications in Genetics and Molecular Biology, De Gruyter, 2018, 17 (5), ⟨10.1515/sagmb-2017-0077⟩
Statistical Applications in Genetics and Molecular Biology, De Gruyter, 2018, ⟨10.1515/sagmb-2017-0077⟩
Statistical Applications in Genetics and Molecular Biology, De Gruyter, 2018, 17 (5), ⟨10.1515/sagmb-2017-0077⟩
Statistical Applications in Genetics and Molecular Biology, De Gruyter, 2018, ⟨10.1515/sagmb-2017-0077⟩
Omic data are characterized by the presence of strong dependence structures that result either from data acquisition or from some underlying biological processes. Applying statistical procedures that do not adjust the variable selection step to the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c918105dccf33bc2c9fbce3def3d79f9
https://hal-agroparistech.archives-ouvertes.fr/hal-02902041
https://hal-agroparistech.archives-ouvertes.fr/hal-02902041
Autor:
Margaux Bregere, Ricardo J. Bessa
Publikováno v:
IEEE Access, Vol 8, Pp 131949-131966 (2020)
The implementation of efficient demand response (DR) programs for household electricity consumption would benefit from data-driven methods capable of simulating the impact of different tariffs schemes. This paper proposes a novel method based on cond
Externí odkaz:
https://doaj.org/article/575ff4147ee54478aca615402812c385