CUED Publications database

A Bayesian definition of ‘most probable’ parameters

Jin, Y and Biscontin, G and Gardoni, P (2018) A Bayesian definition of ‘most probable’ parameters. Geotechnical Research, 5. pp. 130-142.

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Abstract

© 2018 Published with permission by the ICE under the CC-BY 4.0 license. Since guidelines for choosing 'most probable' parameters in ground engineering design codes are vague, concerns are raised regarding their definition, as well as the associated uncertainties. This paper introduces Bayesian inference for a new rigorous approach to obtaining the estimates of the most probable parameters based on observations collected during construction. Following the review of optimisation-based methods that can be used in back-analysis, such as gradient descent and neural networks, a probabilistic model is developed using Clough and O'Rourke's method for retaining wall design. Sequential Bayesian inference is applied to a staged excavation project to examine the applicability of the proposed approach and illustrate the process of back-analysis.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div D > Geotechnical and Environmental
Depositing User: Cron Job
Date Deposited: 06 Aug 2018 20:11
Last Modified: 27 Oct 2020 06:35
DOI: 10.1680/jgere.18.00027