A Bayesian Approach to Kriging Metamodeling for Computer Experiments

作者：Deng Haisong^*; Shao Wenze; Ma Yizhong

来源：Journal of Advanced Mechanical Design Systems and Manufacturing, 2012, 6(4): 404-419.

DOI：10.1299/jamdsm.6.404

• Computer Experiments
• Metamodeling
• Gaussian Kriging
• Hierarchical Bayesian Prior
• Experimental Designs

In this paper, an efficient and effective Gaussian Kriging metamodeling approach is proposed in the framework of Bayesian maximum a posterior. Different prior densities and particularly, a Jeffreys' noninformative density based hierarchical prior is imposed respectively on the regression coefficients in the mean model and the correlation parameters in the covariance matrix of Gaussian Kriging. And the involved parameters are estimated by the expectation maximization and Fisher's scoring algorithms. Compared against several benchmark and recent methods in literature, the proposed approach is shown capable of simultaneous high prediction accuracy and low computational cost.

• 出版日期2012
• 单位南京理工大学; 南京邮电大学; 南京审计大学