Transfer Method of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning

doi:10.16182/j.issn1004731x.joss.21-0040

Abstract

Abstract:

The scope of operational simulation experiment is usually determined by experts, which costs relatively high. In order to transfer the knowledge of experimental scope selection from historical data of operational simulation experiment to new operational experiment cases, the method of compromised case-based reasoning is proposed. According to the data characteristics of the case, the representation method of the operational simulation experiment case is proposed; according to the structure and attribute characteristics of the case, the hybrid similarity calculation method of subjective and objective comprehensive weighting is proposed; aiming at the problems of retrieval failure and less information content in the retrieval results, the case retrieval method based on compromise strategy is proposed;according to the characteristics of the retrieval results, the method of integrating and transferring retrieval results is proposed. The effectiveness of the method is proved by experimental analysis based on historical data.

Key words: operational simulation experiments, CBR(case-Based reasoning), compromise strategy, case knowledge transfer

CLC Number:

E917

Jun Ma, Jingyu Yang, Xi Wu. Transfer Method of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning[J]. Journal of System Simulation, 2022, 34(7): 1568-1581.

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References 25

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序号	属性名称	属性类型	个数
1	作战区域	连续数值型	4
2	作战样式	枚举型	1
3	红方作战实体总数	离散数值型	1
4	红方作战实体类型总数	离散数值型	1
5	蓝方作战实体总数	离散数值型	1
6	蓝方作战实体类型总数	离散数值型	1
7	实体类型	枚举型	1·e
8	实体指控关系	离散数值型	2·e
9	实体通信关系	离散数值型	2·e
10	实体部署位置	连续数值型	3·e
11	实体行动对象	离散数值型	1·e
12	实验因素范围	区间型	1
13	实验结果数据 (命中情况)	连续数值型	1

属性序号	权重	属性序号	权重
1	0.096 9	8	0.092 5
2	0.070 5	9	0.092 5
3	0.044 1	10	0.110 9
4	0.053 0	11	0.093 2
5	0.035 4	12	0.076 1
6	0.044 3	13	0.084 3
7	0.106 3

实验方案	相似案例个数	检索准确性
1	5.666 7±0.942 8	0.433 3±1.247 2
2	8.333 3±0.471 4	0.633 3±1.247 2
3	9.666 7±0.471 4	0.766 7±0.471 4

实验方案		属性信息量	案例信息量	方案信息量
方案1	测试案例1	0.999 96	0.999 533	0.999 753
	测试案例1	0.999 11	0.999 533
	测试案例2	1.000 00	1.000 000
	测试案例2	1.000 00	1.000 000
	测试案例3	0.999 97	0.999 725
	测试案例3	0.999 48	0.999 725
方案2	测试案例1	0.999 93	0.998 431	0.997 802
	测试案例1	0.996 93	0.998 431
	测试案例2	0.999 91	0.995 317
	测试案例2	0.990 72	0.995 317
	测试案例3	0.999 97	0.999 657
	测试案例3	0.999 34	0.999 657
方案3	测试案例1	0.999 85	0.995 159	0.995 791
	测试案例1	0.990 47	0.995 159
	测试案例2	0.999 89	0.995 276
	测试案例2	0.990 66	0.995 276
	测试案例3	0.999 73	0.996 936
	测试案例3	0.994 15	0.996 936

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