舰船通信网络异常数据的弱关联定位技术
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摘要
在舰船通信网络异常数据的弱关联定位中,由于使用传统弱关联定位技术的定位误差较大,因此提出一种舰船通信网络异常数据的弱关联定位技术,利用Netflow系统对舰船通信网络异常数据进行提取,通过相空间重构技术处理异常数据提取结果,并利用极限学习机进行数据挖掘,建立舰船通信网络异常数据弱关联定位模型,从而实现异常数据的弱关联定位,通过对比实验可知,该技术的最大定位误差比基于支持向量机的异常数据弱关联定位技术低21.1%;比基于特征遗传算法的异常数据弱关联定位技术低16.4%,证明了该技术更适用于舰船通信网络异常数据的弱关联定位。
In the weak correlation positioning of abnormal data in warship communication network, because the positioning error of traditional weak correlation positioning technology is large, a weak correlation positioning technology of abnormal data in warship communication network is proposed. The abnormal data of warship communication network is extracted by Netflow system, and the results of abnormal data extraction are processed by phase space reconstruction technology, and the limit is utilized. The learning machine carries out data mining and establishes a weak association location model of abnormal data in warship communication network, so as to realize the weak association location of abnormal data.Through comparative experiments, it can be seen that the maximum location error of the technology is 21.1% lower than that of the weak association location technology based on support vector machine and 16.4% lower than that of the weak association location technology based on feature genetic algorithm, which proves the technology. The technique is more suitable for weak correlation location of abnormal data in warship communication network.
In the weak correlation positioning of abnormal data in warship communication network, because the positioning error of traditional weak correlation positioning technology is large, a weak correlation positioning technology of abnormal data in warship communication network is proposed. The abnormal data of warship communication network is extracted by Netflow system, and the results of abnormal data extraction are processed by phase space reconstruction technology, and the limit is utilized. The learning machine carries out data mining and establishes a weak association location model of abnormal data in warship communication network, so as to realize the weak association location of abnormal data.Through comparative experiments, it can be seen that the maximum location error of the technology is 21.1% lower than that of the weak association location technology based on support vector machine and 16.4% lower than that of the weak association location technology based on feature genetic algorithm, which proves the technology. The technique is more suitable for weak correlation location of abnormal data in warship communication network.
引文
[1]郑宝林,唐惠康,谭营军.舰船通信网络中的移动脆弱节点定位与实现[J].舰船科学技术, 2017, 12(6A):107–109.
[2]刘勇,姚力波,吴昱舟,等.静轨光学卫星与自动识别系统的目标点迹关联与误差校正[J].电子与信息学报, 2018, 40(47):127–133.
[3]涂拥军,黄高明,李敬辉.编队队形对无源定位数据关联的影响[J].舰船电子对抗, 2008, 31(34):143–144.
[4]张明,刘胜道,赵文春,等.基于图像匹配定位技术的舰船航迹测量方法研究[J].船电技术, 2017, 37(39):111–114.
[2]刘勇,姚力波,吴昱舟,等.静轨光学卫星与自动识别系统的目标点迹关联与误差校正[J].电子与信息学报, 2018, 40(47):127–133.
[3]涂拥军,黄高明,李敬辉.编队队形对无源定位数据关联的影响[J].舰船电子对抗, 2008, 31(34):143–144.
[4]张明,刘胜道,赵文春,等.基于图像匹配定位技术的舰船航迹测量方法研究[J].船电技术, 2017, 37(39):111–114.