Title :

Adaptive Bayesian Algorithms for the Estimation of Source Term in a Complex Atmospheric Release

Author(s) :

Ickowicz, Adrien [Auteur]
LAGIS-SI
Septier, Francois [Auteur]
LAGIS-SI
Armand, Patrick [Auteur]
DAM Île-de-France [DAM/DIF]
Delignon, Yves [Auteur]
LAGIS-SI

Conference title :

15th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes

City :

Madrid

Country :

Espagne

Start date of the conference :

2013-05-06

Book title :

15th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes

Publication date :

2013-05-06

English keyword(s) :

Source term estimation
bayesian inference
Monte-Carlo techniques
adaptive algorithms

HAL domain(s) :

Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Informatique [cs]/Traitement du signal et de l'image [eess.SP]

English abstract : [en]

In this paper, we present an adaptive algorithm for the estimation of source parameters when a release of pollutant in the atmosphere is observed by a sensor network in complex flow field. Due to the error-based observations, ...
Show more >In this paper, we present an adaptive algorithm for the estimation of source parameters when a release of pollutant in the atmosphere is observed by a sensor network in complex flow field. Due to the error-based observations, inverse statistical methods have to be used to perform an estimation of the parameters (position of the source, time and mass of the release) of interest. However, given the complexity of the dispersion model, even with a Gaussian assumption on the sensor-based errors, direct inversion cannot be done. In order to have quick results, classical MCMC, while accurate, is too slow. We then demonstrate the accuracy of using adaptive techniques such as the AMIS (Population Monte-Carlo based). We finally compare the results with the classical MCMC estimation in term of accuracy and velocity of implementation.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL