Efficient Response Surface Modeling using Sensitivity

摘要

Response surface method became one of famous optimization techniques, but its approximation errors give designers many restrictions. In this paper, we will discuss how to construct RSM efficiently and accurately using sensitivity. Classical RSM uses the least squares method to find the best fitting approximation models from the given data. In this research, moving least squares method is adopted for more accurate approximation, and sensitivity data is used for efficiency.