A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers

B. Ait-El-Fquih; J. F. Giovannelli; N. Paul; A. Girard; I. Hoteit

doi:10.1109/SSP.2018.8450720

A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers

B. Ait-El-Fquih, J. F. Giovannelli, N. Paul, A. Girard, I. Hoteit

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper considers the identification of point-like source of groundwater pollution. The ill-posed character of this problem has recently led to the introduction of a regularization approach that combines source parametrization, and penalization of undesirable solutions based on prior information about the source parameters, thereby ending up with a parametric Bayesian estimation framework. In this framework, a stochastic-type Markov Chain Monte Carlo (MCMC) method has been introduced as an approximate computation tool of the posterior mean estimate of both source parameters and variance of the (assumed homogeneous) observation noise. Being in the more general case of inhomogeneous noise, our main goal is to propose a deterministic-type computation method based on the variational Bayesian approach. Simulation results suggest that the proposed scheme can provide comparable estimation accuracy to MCMC while requiring less computational time.

Original language	English (US)
Title of host publication	2018 IEEE Statistical Signal Processing Workshop, SSP 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	208-212
Number of pages	5
ISBN (Print)	9781538615706
DOIs	https://doi.org/10.1109/SSP.2018.8450720
State	Published - Aug 29 2018
Event	20th IEEE Statistical Signal Processing Workshop, SSP 2018 - Freiburg im Breisgau, Germany Duration: Jun 10 2018 → Jun 13 2018

Publication series

Name	2018 IEEE Statistical Signal Processing Workshop, SSP 2018

Conference

Conference	20th IEEE Statistical Signal Processing Workshop, SSP 2018
Country/Territory	Germany
City	Freiburg im Breisgau
Period	06/10/18 → 06/13/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Bayesian estimation
Groundwater pollution
Inverse problem
Point-like source
Variational Bayes

ASJC Scopus subject areas

Signal Processing
Instrumentation
Computer Networks and Communications

Access to Document

10.1109/SSP.2018.8450720

Cite this

Ait-El-Fquih, B., Giovannelli, J. F., Paul, N., Girard, A., & Hoteit, I. (2018). A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers. In 2018 IEEE Statistical Signal Processing Workshop, SSP 2018 (pp. 208-212). Article 8450720 (2018 IEEE Statistical Signal Processing Workshop, SSP 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSP.2018.8450720

@inproceedings{605749e6130140bba08ddddbe991e612,

title = "A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers",

abstract = "This paper considers the identification of point-like source of groundwater pollution. The ill-posed character of this problem has recently led to the introduction of a regularization approach that combines source parametrization, and penalization of undesirable solutions based on prior information about the source parameters, thereby ending up with a parametric Bayesian estimation framework. In this framework, a stochastic-type Markov Chain Monte Carlo (MCMC) method has been introduced as an approximate computation tool of the posterior mean estimate of both source parameters and variance of the (assumed homogeneous) observation noise. Being in the more general case of inhomogeneous noise, our main goal is to propose a deterministic-type computation method based on the variational Bayesian approach. Simulation results suggest that the proposed scheme can provide comparable estimation accuracy to MCMC while requiring less computational time.",

keywords = "Bayesian estimation, Groundwater pollution, Inverse problem, Point-like source, Variational Bayes",

author = "B. Ait-El-Fquih and Giovannelli, {J. F.} and N. Paul and A. Girard and I. Hoteit",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 20th IEEE Statistical Signal Processing Workshop, SSP 2018 ; Conference date: 10-06-2018 Through 13-06-2018",

year = "2018",

month = aug,

day = "29",

doi = "10.1109/SSP.2018.8450720",

language = "English (US)",

isbn = "9781538615706",

series = "2018 IEEE Statistical Signal Processing Workshop, SSP 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "208--212",

booktitle = "2018 IEEE Statistical Signal Processing Workshop, SSP 2018",

address = "United States",

}

Ait-El-Fquih, B, Giovannelli, JF, Paul, N, Girard, A & Hoteit, I 2018, A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers. in 2018 IEEE Statistical Signal Processing Workshop, SSP 2018., 8450720, 2018 IEEE Statistical Signal Processing Workshop, SSP 2018, Institute of Electrical and Electronics Engineers Inc., pp. 208-212, 20th IEEE Statistical Signal Processing Workshop, SSP 2018, Freiburg im Breisgau, Germany, 06/10/18. https://doi.org/10.1109/SSP.2018.8450720

A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers. / Ait-El-Fquih, B.; Giovannelli, J. F.; Paul, N. et al.
2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 208-212 8450720 (2018 IEEE Statistical Signal Processing Workshop, SSP 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers

AU - Ait-El-Fquih, B.

AU - Giovannelli, J. F.

AU - Paul, N.

AU - Girard, A.

AU - Hoteit, I.

PY - 2018/8/29

Y1 - 2018/8/29

N2 - This paper considers the identification of point-like source of groundwater pollution. The ill-posed character of this problem has recently led to the introduction of a regularization approach that combines source parametrization, and penalization of undesirable solutions based on prior information about the source parameters, thereby ending up with a parametric Bayesian estimation framework. In this framework, a stochastic-type Markov Chain Monte Carlo (MCMC) method has been introduced as an approximate computation tool of the posterior mean estimate of both source parameters and variance of the (assumed homogeneous) observation noise. Being in the more general case of inhomogeneous noise, our main goal is to propose a deterministic-type computation method based on the variational Bayesian approach. Simulation results suggest that the proposed scheme can provide comparable estimation accuracy to MCMC while requiring less computational time.

AB - This paper considers the identification of point-like source of groundwater pollution. The ill-posed character of this problem has recently led to the introduction of a regularization approach that combines source parametrization, and penalization of undesirable solutions based on prior information about the source parameters, thereby ending up with a parametric Bayesian estimation framework. In this framework, a stochastic-type Markov Chain Monte Carlo (MCMC) method has been introduced as an approximate computation tool of the posterior mean estimate of both source parameters and variance of the (assumed homogeneous) observation noise. Being in the more general case of inhomogeneous noise, our main goal is to propose a deterministic-type computation method based on the variational Bayesian approach. Simulation results suggest that the proposed scheme can provide comparable estimation accuracy to MCMC while requiring less computational time.

KW - Bayesian estimation

KW - Groundwater pollution

KW - Inverse problem

KW - Point-like source

KW - Variational Bayes

UR - http://www.scopus.com/inward/record.url?scp=85053838430&partnerID=8YFLogxK

U2 - 10.1109/SSP.2018.8450720

DO - 10.1109/SSP.2018.8450720

M3 - Conference contribution

AN - SCOPUS:85053838430

SN - 9781538615706

T3 - 2018 IEEE Statistical Signal Processing Workshop, SSP 2018

SP - 208

EP - 212

BT - 2018 IEEE Statistical Signal Processing Workshop, SSP 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 20th IEEE Statistical Signal Processing Workshop, SSP 2018

Y2 - 10 June 2018 through 13 June 2018

ER -

Ait-El-Fquih B, Giovannelli JF, Paul N, Girard A, Hoteit I. A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers. In 2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 208-212. 8450720. (2018 IEEE Statistical Signal Processing Workshop, SSP 2018). doi: 10.1109/SSP.2018.8450720

A Variational Bayesian Estimation Scheme for Parametric Point-Like Pollution Source of Groundwater Layers

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this