A novel improvement of Kriging surrogate model
Aircraft Engineering and Aerospace Technology
ISSN: 0002-2667
Article publication date: 19 December 2018
Issue publication date: 15 August 2019
Abstract
Purpose
This paper aims to introduce a method based on the optimizer of the particle swarm optimization (PSO) algorithm to improve the efficiency of a Kriging surrogate model.
Design/methodology/approach
PSO was first used to identify the best group of trend functions and to optimize the correlation parameter thereafter.
Findings
The Kriging surrogate model was used to resolve the fuselage optimization of an unmanned helicopter.
Practical implications
The optimization results indicated that an appropriate PSO scheme can improve the efficiency of the Kriging surrogate model.
Originality/value
Both the STANDARD PSO and the original PSO algorithms were chosen to show the effect of PSO on a Kriging surrogate model.
Keywords
Acknowledgements
The authors gratefully acknowledge the support of the National Natural Science Foundation of China (No.91538204) and the Aerospace Science and Technology Fund.
Citation
He, W., Xu, Y., Zhou, Y. and Li, Q. (2019), "A novel improvement of Kriging surrogate model", Aircraft Engineering and Aerospace Technology, Vol. 91 No. 7, pp. 994-1001. https://doi.org/10.1108/AEAT-06-2018-0157
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited