计算机工程2018，Vol.44Issue(3)：109-113,118,6.DOI:10.3969/j.issn.1000-3428.2018.03.019
WSN中基于分簇的模糊加权数据融合算法
Fuzzy-weighted Algorithm for Data Fusion Based on Clustering in WSN
摘要
Abstract
In order to ensure the accuracy and real-time of data in data collection and transmission,a Fuzzy-Weighted Algorithm for Data Fusion (FWADF) based on clustering is proposed.Fuzzy logic controller is used to analyze the reliability of node data in the cluster to ensure the credibility of the data.At the same time,the priority of data is added to reduce the network delay.In the cluster,fuzzy-weighted matrix method is used to improve the accuracy of the data.Experimental result with NS-2 simulation tool shows that,the time delay of arriving at the base station is the shortest under the same data traffic,when the nodes collect the same amount of data,compared with the algorithms such as Proposed DF and VWFFA,FIM,the average accuracy rate of the data obtained by base stations is increased by 5.0％,16.1％ and 9.5％ respectively.关键词
无线传感器网络/数据融合/模糊加权/实时性/可信度Key words
Wireless Sensor Network (WSN)/data fusion/fuzzy-weighted/real-time/credibility分类
信息技术与安全科学引用本文复制引用
任秀丽,吉鹏硕..WSN中基于分簇的模糊加权数据融合算法[J].计算机工程,2018,44(3):109-113,118,6.基金项目
辽宁省教育厅科学研究一般项目(LYB201617,L2015204). （LYB201617,L2015204）
