Uncertainty modelling on coupled models using minimum information methods

Bedford, Tim and Wilson, Kevin and Daneshkhah, Alireza (2012) Uncertainty modelling on coupled models using minimum information methods. In: PSAM11 & ESREL 2012, 2012-06-25 - 2012-06-29.

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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.

Creators(s):	Bedford, Tim ORCID: https://orcid.org/0000-0002-3545-2088, Wilson, Kevin and Daneshkhah, Alireza;
Item type:	Conference or Workshop Item(Paper)
ID code:	40919
Keywords:	minimum information, coupled models, expert judgement, probabilistic risk analysis, Management. Industrial Management
Subjects:	Social Sciences > Industries. Land use. Labor > Management. Industrial Management
Department:	Strathclyde Business School > Management Science
Depositing user:	Pure Administrator
Date deposited:	17 Aug 2012 14:11
Last modified:	01 Jan 2021 07:38
Related URLs:	Event
URI:	https://strathprints.strath.ac.uk/id/eprint/40919
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