指挥控制与仿真2024，Vol.46Issue(2)：29-34,6.DOI:10.3969/j.issn.1673-3819.2024.02.005
基于BP神经网络的水下对抗预测模型研究
Research on underwater confrontation prediction model based on BP neural network
罗立峰 1张静远 1华明 2封皓君 2于莹1
作者信息
- 1. 海军工程大学, 湖北 武汉 430033
- 2. 92858 部队, 浙江 宁波 315812
- 折叠
摘要
Abstract
Aiming at the difficulties in the quantitative verification and evaluation of underwater countermeasures for our un-derwater platform and the lack of a guided maneuvering evasive combat model,a prediction model of underwater counter-measures based on big data learning is designed.Firstly,the underwater countermeasure modeling of the underwater platform is carried out,and the large data set of avoidance probability is obtained by several rounds of simulation based on Monte Carlo method.At the same time,in order to solve the problem of poor time efficiency under massive simulation,BP neural network prediction algorithm is proposed for big data learning to provide accurate,fast and visual antagonistic results.The test results show that under the test environment set in this paper,the average prediction error of BP neural network predic-tion algorithm is 7.28%respectively,which can effectively predict the avoidance probability of the underwater platform and provide data support for the commander's command decision.关键词
软对抗/大数据/对抗预测模型/规避概率Key words
soft confrontation/big data/adversarial prediction model/avoidance probability引用本文复制引用
罗立峰,张静远,华明,封皓君,于莹..基于BP神经网络的水下对抗预测模型研究[J].指挥控制与仿真,2024,46(2):29-34,6.
