Gaussian Process Models for Computer Experiments With Qualitative and Quantitative Factors
Gaussian Process Models for Computer Experiments With Qualitative and Quantitative Factors
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DOI：
10.1198/004017008000000262
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发表时间：
2008-08
期刊：
影响因子：
2.5
通讯作者：
Peter Z. G. Qian;Huaiqin Wu;C. F. J. Wu
中科院分区：
文献类型：
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作者：
Peter Z. G. Qian;Huaiqin Wu;C. F. J. Wu
用定性和定量因素进行建模实验是计算机建模的重要问题。我们提出了一个框架，用于构建合并两种因素的高斯流程模型。开发这些新模型的关键是一种与定性和定量因素构建相关函数的方法。为提出的模型开发了迭代估计程序。现代优化技术用于估算中，以确保构造相关函数的有效性。提出的方法用涉及已知功能的示例和一个真实示例进行了说明，用于建模数据中心的热分布。
Modeling experiments with qualitative and quantitative factors is an important issue in computer modeling. We propose a framework for building Gaussian process models that incorporate both types of factors. The key to the development of these new models is an approach for constructing correlation functions with qualitative and quantitative factors. An iterative estimation procedure is developed for the proposed models. Modern optimization techniques are used in the estimation to ensure the validity of the constructed correlation functions. The proposed method is illustrated with an example involving a known function and a real example for modeling the thermal distribution of a data center.