A novel improvement of Kriging surrogate model. Issue 7 (19th December 2018)

• Record Type: Journal Article
• Authors: He, Wei; Xu, Yuanming; Zhou, Yaoming; Li, Qiuyue
• Is Part Of: Aircraft engineering and aerospace technology. Volume 91:Issue 7(2019)
• Page Start: 994
• Page End: 1001
• Publication Date: 2018-12-19
• Subjects: Particle swarm optimization -- Fuselage optimization -- Kriging surrogate model -- Unmanned helicopter; Aerospace engineering -- Periodicals; Aeronautics -- Systems engineering -- Periodicals; Astronautics -- Systems engineering -- Periodicals; Airplanes -- Equipment and supplies -- Periodicals; Space vehicles -- Equipment and supplies -- Periodicals; Aerospace industries -- Periodicals; 629.1
• DOI: 10.1108/AEAT-06-2018-0157
• Languages: English
• ISSNs: 1748-8842

Abstract

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.