Uncertainty modelling on coupled models using minimum information methods

Tim Bedford; Kevin J. Wilson; Alireza Daneshkhah

Uncertainty modelling on coupled models using minimum information methods

Tim Bedford, Kevin J. Wilson, Alireza Daneshkhah

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

Abstract

Probabilistic inversion is used to take expert uncertainty assessments about observable model outputs and build from them a distribution on the model parameters that captures the uncertainty expressed by the experts. In this paper we look at ways to use minimum information methods to do this, focussing in particular on the problem of ensuring consistency between expert assessments about differing variables, either as outputs from a single model, or potentially as outputs along a chain of models. The paper shows how such a problem can be structured and then illustrates the method with an example involving atmospheric dispersion and deposition.

Original language	English
Title of host publication	11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012
Pages	6801-6810
Number of pages	10
Volume	8
Publication status	Published - 1 Dec 2012
Externally published	Yes
Event	11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012 - Helsinki, Finland Duration: 25 Jun 2012 → 29 Jun 2012

Conference

Conference	11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012
Country/Territory	Finland
City	Helsinki
Period	25/06/12 → 29/06/12

Keywords

Coupled models
Expert judgement
Minimum information
Probabilistic risk analysis

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality

Cite this

Uncertainty modelling on coupled models using minimum information methods. / Bedford, Tim; Wilson, Kevin J.; Daneshkhah, Alireza.
11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012. Vol. 8 2012. p. 6801-6810.

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

Bedford, T, Wilson, KJ & Daneshkhah, A 2012, Uncertainty modelling on coupled models using minimum information methods. in 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012. vol. 8, pp. 6801-6810, 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012, Helsinki, Finland, 25/06/12.

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AB - Probabilistic inversion is used to take expert uncertainty assessments about observable model outputs and build from them a distribution on the model parameters that captures the uncertainty expressed by the experts. In this paper we look at ways to use minimum information methods to do this, focussing in particular on the problem of ensuring consistency between expert assessments about differing variables, either as outputs from a single model, or potentially as outputs along a chain of models. The paper shows how such a problem can be structured and then illustrates the method with an example involving atmospheric dispersion and deposition.

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BT - 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012

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Y2 - 25 June 2012 through 29 June 2012

ER -

Uncertainty modelling on coupled models using minimum information methods

Abstract

Conference

Keywords

ASJC Scopus subject areas

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