Browse

Towards a Bayesian framework for model validation

Cited 0 time in Web of Science Cited 0 time in Scopus
Authors
Gray, Ander; Patelli, Edoardo
Issue Date
2019-05-26
Citation
13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019
Abstract
In this paper we discuss some concepts and a methodology of a Bayesian framework for model validation under uncertainty, which produces a probabilistic value for a models validity and may be used in the design of validation experiments. By using a stochastic metric as a measure of the distance between experiment and prediction, we update a validation distribution. We show this in practice using a simple numerical experiment and discuss the current shortcomings of the method. We finally discuss the role of information entropy in designing validation experiments.
Language
English
URI
https://hdl.handle.net/10371/153480
DOI
https://doi.org/10.22725/ICASP13.347
Files in This Item:
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Civil & Environmental Engineering (건설환경공학부)ICASP13
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse