基于改进灰色关联分析的航天产品性能样机仿真结果一致性验证方法

doi:10.12305/j.issn.1001-506X.2023.09.16

摘要/Abstract

摘要：

灰色关联分析法因其计算简单、不要求大样本容量等诸多优点被广泛应用于仿真模型验证领域, 但邓氏关联度模型存在无法判断序列距离的弊端, 容易造成仿真验证结果的误判。为了提高使用灰色关联分析法验证仿真结果可靠性的准确度, 提出一种用以判断数据序列之间距离的距离分析方法。在验证航天产品性能样机仿真结果一致性时, 将距离分析方法与灰色关联分析法相结合, 形成考虑序列距离的灰色关联分析法, 从曲线的形状与位置两个方面同时判断两组序列的一致性, 从而提高了验证结果的准确度与可靠性。

关键词: 灰色关联分析, 仿真结果验证, 距离分析, 性能样机

Abstract:

The grey correlation analysis method is widely used in the field of simulation model validation due to its advantages such as simple calculation and not requiring large sample size. However, the Deng correlation degree model has the drawback of being unable to determine the sequence distance, which can easily lead to misjudgment of simulation validation results. In order to improve the accuracy of using grey correlation analysis to verify the reliability of simulation results, a distance analysis method is proposed to determine the distance between data sequences. When verifying the consistency of simulation results for aerospace product performance prototypes, the distance analysis method is combined with the grey correlation analysis method to form a grey correlation analysis method that considers sequence distance. It can judge the consistency of two sets of sequences from both the shape and position of the curve, improving the accuracy and reliability of the verification results.

Key words: grey relational analysis (GRA), simulation result validation, distance analysis, performance prototype

中图分类号:

TP391.9

高山, 智永锋, 张普, 左轩. 基于改进灰色关联分析的航天产品性能样机仿真结果一致性验证方法[J]. 系统工程与电子技术, 2023, 45(9): 2777-2783.

Shan GAO, Yongfeng ZHI, Pu ZHANG, Xuan ZUO. Consistency validation method of simulation results based on improved grey relational analysis for aerospace product performance prototype[J]. Systems Engineering and Electronics, 2023, 45(9): 2777-2783.

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	公理名称	公理描述
1	规范性	0≤γ(x₀(k), x_i(k))≤1 γ(X₀, X_i)=1 $ \Leftrightarrow $ X₀=X_i
2	整体性	对任意X_i, X_j∈X, i≠j都有γ(X_i, X_j)≠γ(X_j, X_i)
3	偶对称性	对任意X_i, X_j∈X γ(X_i, X_j)=γ(X_j, X_i) $ \Leftrightarrow $ X={X_i, X_j}
4	接近性	\|x₀(k)－x_i(k)\|越小, γ(x₀(k), x_i(k))越大

方法	序列	γ	γ_C	一致性
GRA	X₁	1	-	一致
	X₂	1	-	一致
	X₃	1	-	一致
考虑距离的GRA	X₁	-	0.84	不一致
	X₂	-	0.84	不一致
	X₃	-	0.84	不一致

方法	序列	γ	γ_C	一致性
GRA	X₁	0.92	-	一致
	X₂	0.91	-	一致
	X₃	0.92	-	一致
考虑距离的GRA	X₁	-	0.60	不一致
	X₂	-	0.59	不一致
	X₃	-	0.60	不一致

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