Optimal sampling strategy for high-density polyethylene production processes

被引：0
|
作者：
Yin P. [1 ]
Chen W.-F. [1 ]
机构：
[1] School of Information Engineering, Zhejiang University of Technology, Hangzhou
来源：
Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities | 2022年 / 36卷 / 05期
关键词：
high-density polyethylene; Latin hypercube sampling; optimal sampling; parameter estimation; parameter subset selection;
D O I：
10.3969/j.issn.1003-9015.2022.05.016
中图分类号：
学科分类号：
摘要：
A large number of sampling points are required to ensure the accuracy of parameter estimation, which leads to high cost of sample analysis. An optimal sampling strategy was thus put forward based on Latin hypercube sampling to reduce the number of sampling points and ensure parameter estimation accuracy. By solving corresponding optimal sampling sub-problems with the candidate values of parameter space by Latin hypercube sampling, the selection frequency of each potential sampling point was constructed in the optimal sampling strategy. Sampling points were selected by virtue of heuristic strategy and iterative enhancement strategy, and parameter estimation was achieved. The numerical simulation results show that the sampling strategy proposed can greatly reduce the number of sampling points while ensuring parameter estimation accuracy. In addition, it is more stable than the optimal sampling method based on random sampling. © 2022 Zhejiang University. All rights reserved.
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页码：738 / 747
页数：9
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