文献类型：期刊文献

英文题名：Method of Hybrid Adaptive Sampling for the Kriging Metamodel and Application in the Hydropurification Process of Industrial Terephthalic Acid

作者：Cheng, Hui[1];Cheng, Liang[1];Li, Zhi[1];Ye, Zhencheng[1];Yang, Minglei[1]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2020

卷号：59

期号：43

起止页码：19345

外文期刊名：INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

收录：;EI(收录号：20204409439627);WOS:【SCI-EXPANDED(收录号:WOS:000586870700027)】；

基金：This research was funded by the National Natural Science Foundation of China (Basic Science Center Program: 61988101), International (Regional) Cooperation and Exchange Project (61720106008), the National Natural Science Fund for Distinguished Young Scholars (61725301), the National Natural Science Foundation of China (61803158, 61873093), and the Fundamental Research Funds for the Central Universities (222201814047).

语种：英文

外文关键词：Nearest neighbor search - Design of experiments - Benchmarking - Reliability analysis

摘要：The high-fidelity model is not easy to analyze and optimize because of the high computational cost. When the classical design of experiments is applied to construct the metamodel to replace such a computationally intensive model for analysis or optimization, it usually needs more samples compared with hybrid adaptive sampling to ensure the reliability of the metamodel due to ignoring the system information. In this study, considering the general feature of the chemical model, a new method of hybrid adaptive sampling named hybrid adaptive sampling algorithm based on scores (HASAS) is proposed on the basis of k-nearest neighbor for exploration and nearest neighbor expected improvement for exploitation to enhance the global quality of the metamodel. Furthermore, a weight coefficient is introduced to balance exploration and exploitation during sample placement. Sixteen benchmark cases are utilized to evaluate the performance of the HASAS and four other hybrid adaptive methods. Results show that with the same number of samples, HASAS can perform well in terms of global accuracy on most of them. The effect of the number of initial sample points on HASAS is also discussed. Finally, it is applied for the construction of the Kriging for the hydropurification process of a typical chemical (terephthalic acid) and sensitivity of each variable is done with the metamodel.