计算机科学
水下
反击
对手
威胁评估
贝叶斯网络
战场
贝叶斯概率
推论
人工智能
等级制度
数据挖掘
机器学习
计算机安全
地质学
海洋学
经济
古代史
法学
历史
市场经济
政治学
作者
Danyi Li,Meiqin Liu,Senlin Zhang
出处
期刊:Chinese Control Conference
日期:2021-07-26
卷期号:: 3363-3367
被引量:3
标识
DOI:10.23919/ccc52363.2021.9549765
摘要
Underwater targets are used more and more frequently in modern ocean battlefield. It is important to assess the threat from an enemy target after it is detected immediately, in order to prepare quick counterattack and defense. This paper proposes a method for underwater target threat assessment based on Bayesian Network. The threat model uses a hierarchy view for threat factors. All factors are divided into three parts: environment, target space and target fire. Each part contains several detailed factors, which are arranged based on their causal relationships. These factors are applied into the Bayesian Network and the probability of threat is calculated through Bayesian inference. Finally, a simulation is conducted and the method can effectively assess the target threat. The model has a relatively good performance and can generate the assessment with low time cost.
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