基于改进决策树的导航系统故障诊断的研究  

Research of Fault Diagnosis of Navigation System Based on Improved Decision Tree

作　　者：刘东涛 LIU Dongtao

机构地区：[1]海装沈阳局驻大连地区第一军事代表室,大连116000

出　　处：《现代导航》2022年第5期334-338,共5页Modern Navigation

摘　　要：提出了一种基于改进决策树的导航系统故障诊断方法。该方法首先将导航数据的初始属性按照信息增益率进行排序,然后利用神经网络对初始属性进行裁剪处理,最后用裁剪后的属性建立最小决策树,并建立分类规则。与传统的决策树分类算法相比,此方法通过利用信息增益筛选属性,直接生成最小规模决策树,避免了决策树的剪枝处理过程。实验表明,此方法与传统决策树算法相比,时间开销更小,诊断精度也有所提高。A new navigation system troubleshooting method based on improved decision tree algorithm is proposed.Firstly,the original attributes of navigation data are sorted by information gain rate(IGR).Then the sorted attributes are clipped with neural network.Finally,the minimum decision tree is built with the clipped attributed,as well as the classification rules.Compared with the traditional decision tree algorithm,this improve decision tree picks attributes with IGR,and build the minimum decision tree directly,which can avoid the node clipping deal.The experiments indicated that this algorithm need shorter extraction time,and get higher precision.

关 键 词：导航系统 故障诊断 决策树 神经网络 信息增益率 

分 类 号：TN967[电子电信—信号与信息处理]