An Adaptive Copula-Based Approach for Model Bias Characterization

Paper #:
  • 2015-01-0455

Published:
  • 2015-04-14
DOI:
  • 10.4271/2015-01-0455
Citation:
Pan, H., Xi, Z., and Yang, R., "An Adaptive Copula-Based Approach for Model Bias Characterization," SAE Int. J. Mater. Manf. 8(2):315-321, 2015, doi:10.4271/2015-01-0455.
Pages:
7
Abstract:
A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.
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