Innovative stochastic modeling of residential exposure due to a WiFi source placed in uncertain position

This study focused on the evaluation of the electric field 2D spatial distribution of the E-field in a one-floor apartment when a WiFi source is placed in uncertain position. An innovative approach that combines Principal Component Analysis and Kriging model in order to build space-dependent surrogate models was applied and validated. Preliminary results showed the feasibility of the approach.

Domaines

Santé publique et épidémiologie Machine Learning [stat.ML] Applications [stat.AP] Modélisation et simulation Recherche opérationnelle [math.OC] Traitement du signal et de l'image [eess.SP] Statistiques [math.ST]

Fichier principal

Bioem_2019_IndoorExposure.pdf (743.13 Ko)

Origine	Fichiers produits par l'(les) auteur(s)

Laurent Le Brusquet : Connectez-vous pour contacter le contributeur

https://hal.science/hal-02439223

Soumis le : mardi 14 janvier 2020-15:07:03

Dernière modification le : mercredi 30 octobre 2024-20:42:05

Archivage à long terme le : mercredi 15 avril 2020-19:10:37

Dates et versions

hal-02439223 , version 1 (14-01-2020)

Identifiants

HAL Id : hal-02439223 , version 1

Citer

Emma Chiaramello, David Plets, Serena Fiocchi, Marta Bonato, Gabriella Tognola, et al.. Innovative stochastic modeling of residential exposure due to a WiFi source placed in uncertain position. BioEM2019 - Annual Joint Meeting of the Bioelectromagnetics Society (BEMS) and the European BioElectromagnetics Association (EBEA), Jun 2019, Montpellier, France. ⟨hal-02439223⟩

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Collections

CNRS SUP_LSS SUP_SIGNAUX CENTRALESUPELEC TDS-MACS UNIV-PARIS-SACLAY GS-ENGINEERING GS-COMPUTER-SCIENCE

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