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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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 ![]() | Item type: | Conference or Workshop Item(Paper) |
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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: | |
URI: | https://strathprints.strath.ac.uk/id/eprint/40919 |
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