基于贝叶斯网络的海上目标识别  

Identify Object on Sea Based on Bayes Network

作　　者：肖秦琨[1] 

机构地区：[1]西安工业学院电子信息学院,陕西西安710032

出　　处：《微机发展》2005年第10期152-154,共3页Microcomputer Development

摘　　要：贝叶斯分类器是使错误分类概率最小的最优方法,但必须具备先验知识,计算量也很大,从而增加了实时应用的复杂性。提出基于贝叶斯网络海上目标识别,结合贝叶斯网络对不确定事件强的推理作用,以及贝叶斯理论的数学基础,应用图形模式,使得计算量大大简化,降低了实用的复杂性。A classify tool based on hayes theory is best way that make minimal error. If want to use this way, must master enough prior knowledge. That waster lots of time to calculate. This paper thinks out a good idea to identify an object on sea based on hayes network. It is no bad way because of inference and express method of unceitain knowledge as well as graphics mode. So this method uses less time to get result.

关 键 词：贝叶斯网络 不确定推理 目标识别 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]