Bhattacharyya distance: A novel uncertainty quantification metric

What is it about?

Uncertainty treatment is a popular tendency for model updating to extend this campaign from the deterministic sense to the stochastic sense. This work proposes a novel uncertainty quantification metric based on the Bhattacharyya distance with the purpose to capture more uncertainty information. An excited advantage of the Bhattacharyya distance is demonstrated when solving the well-known NASA Langley Uncertainty Quantification Challenge problem.

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Why is it important?

An impressive feature of this work is that the Bhattacharyya distance metric can be conveniently embedded into a Bayesian updating frame similar to the deterministic updating. We only need to replace the typical Euclidian distance using the novel Bhattacharyya distance within this framework, and then a completely different result is achieved with more comprehensive uncertainty treatment.

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