Gradient-enhanced high dimensional model representation via Bayesian inference

作者：

Highlights：

• HDMR surrogate model are developed based on Bayesian inference technique.

• An efficient method for HDMR model integrating gradient information is presented.

• Eight benchmark examples are used to validate the effectiveness of the method.

摘要

•HDMR surrogate model are developed based on Bayesian inference technique.•An efficient method for HDMR model integrating gradient information is presented.•Eight benchmark examples are used to validate the effectiveness of the method.

论文关键词：Surrogate model,Bayesian inference,Gaussian process,High dimensional model representation

论文评审过程：Received 9 September 2018, Revised 19 June 2019, Accepted 28 July 2019, Available online 31 July 2019, Version of Record 11 October 2019.

论文官网地址：https://doi.org/10.1016/j.knosys.2019.104903