摘要
针对传统方法对双层网络中心数据挖掘方法中存在数据输出特征分辨率低、耗时长等问题,提出上行链路干扰下双层网络中心数据挖掘方法。评估不同属性数据度量值,获取上行链路干扰下双层网络中心数据的谱特征分布,根据关联规则特征量构建双层网络中心数据分布存储模型;结合特征提取结果进行数据挖掘;采用射频标签识别技术量化双层网络中心数据向量,完成数据挖掘的干扰抑制,根据关联知识融合结果进行双层网络中心数据的相关性融合,结合自适应滤波方法进行上行链路干扰抑制,实现上行链路干扰下双层网络中心数据挖掘优化。仿真结果表明,采用所提方法进行上行链路干扰下双层网络中心数据挖掘的精度较高,且耗时较短。
At present, low resolution and high time consumption in traditional data mining methods are the main problems. In this article, a method of mining data from a double-layer network center with uplink interference was put forward. At first, the measurement values of different attribute data were assessed to obtain the distribution of spectrum features of the data of a double-layer network center with uplink interference. According to the feature quantity of association rule, the distributed storage model of the data in a double-layer network center was constructed. Based on the results of feature extraction, the data was mined. And then, the RFID technology was used to quantify the data vector in a double-layer network center and thus to complete the interference suppression for data mining. According to the results of knowledge fusion, the correlations between the data in a double-layer network center were fused. Finally, the adaptive filtering method was used to suppress the uplink interference, thus realizing the data mining optimization. Simulation results prove that the proposed method has higher accuracy and lower time consumption in mining the data from a double-layer network center with uplink interference.
作者
冀江瑀
陈秀波
JI Jiang-yu;CHEN Xiu-bo(School of Cyberspace Security,Beijing University of Posts and Teleco mmunications,Beijing 102206,China;Beijing University of Posts and Teleco mmunications,Information Security Center of Cyberspace Security College,Beijing 102206,China)
出处
《计算机仿真》
北大核心
2022年第6期386-390,共5页
Computer Simulation
关键词
上行链路干扰
双层网络
中心数据
挖掘
自适应滤波方法
Uplink interference
Double layer network
Central data
Mining
Adaptive filtering method
