一种基于ML-PMRF的复杂仿真系统可信度智能分配方法

doi:10.12305/j.issn.1001-506X.2025.05.14

Abstract

Abstract:

In order to ensure that the complex simulation system can meet the credibility requirements, the credibility of each simulation sub-system should be determined at the beginning of the construction of the complex simulation system to shorten the development cycle. Therefore, a complex simulation system intelligent credibility allocation method is proposed, which can obtain the credibility allocation results of each simulation sub-system under the condition of the known whole credibility of the complex simulation system. According to the composition and structure of the complex simulation system, the credibility allocation model of the complex simulation system is proposed based on the multi-layer pairwise Markov random field (ML-PMRF). Based on the maximum a posteriori inference and the discrete glowworm swarm optimization, an intelligent inference method for ML-PMRF is proposed. The effectiveness and rationality of the proposed method are verified by practical examples and comparative experiments.

Key words: complex simulation system, credibility allocation, multi-layer pairwise markov random field (ML-PMRF), intelligence inference

CLC Number:

TP391.9

Huan ZHANG, Wei LI, Bing ZHANG, Ping MA, Ming YANG. An intelligent credibility allocation method based on ML-PMRF for complex simulation systems[J]. Systems Engineering and Electronics, 2025, 47(5): 1516-1524.

Figures/Tables 8

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References 33

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仿真子系统可信度	智能推理方法	LBP	ICM
C_{sub, 1}	0.75	0.78	0.76
C_{sub, 2}	0.74	0.75	0.74
C_{sub, 3}	0.88	0.90	0.88
C_{sub, 4}	0.88	0.90	0.88
C_{sub, 5}	0.86	0.87	0.86
C_{sub, 6}	0.75	0.79	0.75
C_{sub, 7}	0.80	0.81	0.80
C_{sub, 8}	0.76	0.76	0.76
C_{sub, 9}	0.76	0.76	0.74
C_{sub, 10}	0.90	0.88	0.87
C_{sub, 11}	0.80	0.80	0.80
C_{sub, 12}	0.80	0.80	0.77
C_{sub, 13}	0.74	0.74	0.73

推理方法	目标函数最小值
智能推理方法	276.23
LBP	283.22
ICM	283.51

节点变量	分配结果	先验概率分布
作战空域	0.80	N(0.8, 0.1)
杀伤概率	0.67	N(0.65, 0.08)
目标综合识别概率	0.83	N(0.83, 0.05)
多目标分配能力	0.90	U(0.9, 1.0)
数据传输准确度	0.80	U(0.75, 0.9)
链路连通率	0.78	N(0.77, 0.06)

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An intelligent credibility allocation method based on ML-PMRF for complex simulation systems

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