基于Kriging模型的稳健参数设计

doi:10.12305/j.issn.1001-506X.2023.07.38

Abstract

Abstract:

For robust parameter optimization in complex engineering systems, a new sequential optimization design method based on Kriging surrogate model is proposed. Firstly, the minimum predicted mean value of the Kriging model is used to replace the actual observed minimum response value to consider the noise. Secondly, the prediction variance of the addition criterion is modified to make it converge with sufficient sample volume. Finally, the effectiveness of the proposed method is verified by classic low dimensional and high dimensional nonlinear numerical and engineering examples. The results show that the proposed method can obtain better global solutions with fewer addition times, and has stronger global optimization ability and robustness compared to existing traditional addition criteria.

Key words: Kriging model, sequential optimization design, noise evaluation, expected improvement, robust parameter design

CLC Number:

F273.2

Chunfeng DING, Jianjun WANG. Robust parameter design based on Kriging model[J]. Systems Engineering and Electronics, 2023, 45(7): 2269-2279.

Figures/Tables 12

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References 32

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变量	名称	下界	上界
r_w	钻孔半径/m	0.05	0.15
r	影响半径/m	100.00	50 000.00
T_u	上部含水层渗透率/(m²/yr)	63 070.00	115 600.00
H_u	上部含水层电位头/m	990.00	1 110.00
T_l	下部含水层渗透率/(m²/yr)	63.10	116.00
H_l	下部含水层电位头/m	700.00	820.00
L	钻孔长度/m	1 120.00	1 680.00
K_w	钻孔水力传导率/(m/yr)	1 500.00	15 000.00

数值算例	优化方法	评价指标
数值算例	优化方法	OE1	OE2	OE3
算例1	EI	-0.031 1	66.466 7	0.006 2
	IECI	-0.037 4	60.666 7	0.000 7
	NIECI	-0.065 7	57.633 3	0.000 2
算例2	EI	-2.861 2	179.333 3	0.004 7
	IECI	-2.997 2	162.566 7	0.000 4
	NIECI	-3.080 9	139.300 0	0.000 4
算例3	EI	2.720 7	98.766 7	0.002 7
	IECI	2.651 9	102.300 0	0.027 2
	NIECI	2.224 6	93.700 0	4.187 6e-05

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Robust parameter design based on Kriging model

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