Error Analysis of Approximated PCRLBs for Nonlinear Dynamics

Autor: Lei, Ming, Del Moral, Pierre, Baehr, Christophe

In practical nonlinear filtering, the assessment of achievable filtering performance is important. In this paper, we focus on the problem of efficiently approximate the posterior Cramer-Rao lower bound (CRLB) in a recursive manner. By using Gaussian

Externí odkaz: http://arxiv.org/abs/1005.5348

FAIRification of Multidimensional and Tabular Data by Instantiating a Core Semantic Model with Domain Knowledge: Case of Meteorology

Autor: Trojahn, Cassia, Kamel, Mouna, Annane, Amina, Aussenac-Gilles, Nathalie, Nguyen, Bao-Long, Baehr, Christophe

Publikováno v: Metadata and Semantic Research (MTSR 2022)
16th International Conference on Metadata and Semantics Research (MTSR 2022)
16th International Conference on Metadata and Semantics Research (MTSR 2022), Nov 2022, London, United Kingdom. à paraître

International audience; Open data is exposed in several formats, including tabular format. However, the meaning of columns, that can also be seen as dimensions, is not always explicit what makes difficult the reuse of this data for data consumers. Th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d7ba6ac9c927b997bca43f7cf50357f7
https://hal.science/hal-03872638

SYNOP Data Evaluation Using FAIR Maturity Model

Autor: Annane, Amina, Kamel, Mouna, Trojahn, Cassia, Aussenac-Gilles, Nathalie, Comparot, Catherine, Baehr, Christophe

Publikováno v: [Research Report] IRIT/RR--2021--03--FR, IRIT-Institut de Recherche en Informatique de Toulouse. 2021

SYNOP dataset is one of the open meteorological datasets privided by Météo-France on its data portal. The dataset includes observation data from international surface observation messages circulating on the Global Telecommunication System (GTS) of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::08fb1d7dd19d49eb5ed254ecb877fef0
https://hal.archives-ouvertes.fr/hal-03197115/document

Un modèle sémantique en vue d’améliorer la FAIRisation des données météorologiques

Autor: Annane, Amina, Kamel, Mouna, Aussenac-Gilles, Nathalie, Trojahn, Cassia, Comparot, Catherine, Baehr, Christophe

Publikováno v: Séminaire In-OVIVE
Séminaire In-OVIVE, réseau In-OVIVVE-INRAE, Sep 2021, Paris, France
Journées Francophones d'Ingénierie des Connaissances (IC) Plate-Forme Intelligence Artificielle (PFIA 2021)
Journées Francophones d'Ingénierie des Connaissances (IC) Plate-Forme Intelligence Artificielle (PFIA 2021), Collège SIC (Science de l’Ingénierie des Connaissances) de l’AFIA, Jun 2021, Bordeaux, France. pp.20-29
Actes IC 2021 (@ PFIA 2021)
Journées Francophones d'Ingénierie des Connaissances (IC 2021) @ Plate-Forme Intelligence Artificielle (PFIA 2021)
Journées Francophones d'Ingénierie des Connaissances (IC 2021) @ Plate-Forme Intelligence Artificielle (PFIA 2021), Collège SIC (Science de l’Ingénierie des Connaissances) de l’AFIA, Jun 2021, Bordeaux (en distanciel), France. pp.20-29

Making meteorological data FAIR in order to ease its reuse is a strategic issue because this data is essential to advance research in many fields. This work proposes a semantic model which combines a metadata model and a data model for describing met

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd22cf1b7e1decbe251963746a628b21
https://hal.science/hal-03409597

Real Time Turbulence Estimation Using Doppler Lidar Measurements

Autor: Rottner Lucie, Baehr Christophe

Publikováno v: EPJ Web of Conferences, Vol 119, p 14001 (2016)

A preliminary work on a new way to estimate atmospheric turbulence using high-frequency Doppler lidar measurements is presented. The turbulence estimations are based on wind reconstruction using 3D Doppler lidar observations and a particle filter. Th

Externí odkaz: https://doaj.org/article/963dd03b071b4f9eb83579f3073ceed3