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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    Title :

    An Adaptive Copula-Based Approach for Model Bias Characterization


    Additional title:

    Sae Int. J. Mater. Manf
    Sae International Journal of Materials and Manufacturing


    Contributors:
    Pan, Hao (author) / Yang, Ren-Jye (author) / Xi, Zhimin (author)

    Conference:

    SAE 2015 World Congress & Exhibition ; 2015



    Publication date :

    2015-04-14


    Size :

    7 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English


    Keywords :


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