基于改进型生成对抗网络的指挥信息系统模拟数据生成算法

doi:10.3969/j.issn.1001-506X.2021.01.20

摘要/Abstract

摘要：

针对指挥信息系统模拟训练数据缺乏的问题,提出一种基于改进型生成对抗网络的模拟数据生成算法,构建指挥信息系统履行使命任务支撑能力指标体系,同时提出指挥信息系统非结构化信息处理的映射方式和拟合度因子,修正损失函数,从而提高优化水平。仿真结果表明,所提算法能够生成与原始数据分布相似度较高的数据集,为指挥信息系统全元素的模拟训练提供数据支撑。

关键词: 生成对抗网络, 指挥信息系统, 模拟数据集

Abstract:

Aiming at the lack of simulation training data in command information system, a simulation data generation algorithm based on evolutional generative adversarial networks (EGAN-SDG) is put forword, which constructs the index system of command information system's ability to fulfill missions and tasks. The mapping mode of unstructured information processing in command information system and the fitting factor to modify the loss function to improve the optimization performance are proposed. Simulation results show that the algorithm can generate data sets with high similarity distribution of the original data, and can provide data support for the simulation training of all elements of the command information system.

Key words: generative adversarial network, command information system, simulation data set

中图分类号:

TP391.9

田相轩, 石志强. 基于改进型生成对抗网络的指挥信息系统模拟数据生成算法[J]. 系统工程与电子技术, 2021, 43(1): 163-170.

Xiangxuan TIAN, Zhiqiang SHI. Simulation data generation algorithm based on evolutional generative adversarial networks for command information system[J]. Systems Engineering and Electronics, 2021, 43(1): 163-170.

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ID	22维训练数据
ID	1_1	1_2	1_3	1_4	1_5	1_6	1_7	1_8	1_9	1_10	…	1_22
1	21	12.9	-	-	42.9	-	60.7	-	80	-	…	13.2
2	13.4	8.6	2.42	0.6	5.53	187	52.8	1.1	44	4.31	…	35.3
3	19.6	9.3	3.02	0.5	0.4	293	54.7	1.61	48	-	…	58.1
4	15.4	18.6	1.7	0.44	1.3	140	57.5	0.8	117	-	…	24.5
5	15.5	4.9	2.47	1.03	1.65	135	59.6	1.64	73	-	…	51.4
6	13.1	13.7	2.95	0.49	20.6	258	49.9	0.73	38	-	…	36.3
7	15.5	7	2.72	0.53	0.51	326	62.7	0.7	73	3.1	…	71.5
8	42.5	10.3	4.17	0.53	0.91	174	63.6	1.68	146	-	…	16.3
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	$ \ddots $	⋮

序号	1	2	3	4	5	6	7	…	22
1	1.00	0.21	0.33	0.34	0.25	0.33	0.34	…	0.18
2	0.21	1.00	0.15	0.21	0.24	0.20	0.15	…	0.48
3	0.33	0.15	1.00	0.64	0.25	0.57	0.60	…	0.18
4	0.34	0.21	0.64	1.00	0.21	0.60	0.65	…	0.22
5	0.25	0.24	0.25	0.21	1.00	0.21	0.19	…	0.26
6	0.33	0.20	0.57	0.60	0.21	1.00	0.64	…	0.23
7	0.34	0.15	0.60	0.65	0.19	0.64	1.00	…	0.15
8	0.24	0.22	0.18	0.26	0.31	0.22	0.24	…	0.28
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	$ \ddots $	⋮
22	0.18	0.48	0.18	0.22	0.26	0.23	0.15	…	1.00

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