Data fusion method of industrial internet of things based on fuzzy theory
参考中译:基于模糊理论的工业物联网数据融合方法


          

刊名：International Journal of Internet Manufacturing and Services
作者：Qiaoyun Chen（School of Information Engineering, Jiaozuo University）
Chunmeng Lu（School of Artificial Intelligence, Jiaozuo University）
刊号：738LD067
ISSN：1751-6048
出版年：2023
年卷期：2023, vol.9, no.4
页码：487-501
总页数：15
分类号：TP393
关键词：Clustering routing protocol；Fuzzy theory；Fuzzy classification；Membership function
参考中译：分簇路由协议；模糊理论；模糊分类；隶属函数
语种：eng
文摘：In order to overcome the problem of poor data fusion effect of data fusion method, this paper proposes a data fusion method of industrial internet of things based on fuzzy theory. Firstly, the data acquisition area is divided and the data is collected by the absolute median difference method. Secondly, fuzzy set is constructed to extract data attribute features according to membership function. Then, the trusted data is screened by clustering routing protocol and classified by exponential smoothing method. Finally, the spatial and temporal correlation degree is used to allocate the fusion weights, and the industrial internet of things data fusion is carried out by fuzzy theory. Experimental results show that the classification accuracy of the proposed method can reach 99%, the data fusion rate can reach 99.5%, and the fusion time is only 3.92 s. The proposed method can improve the data fusion effect.
参考中译：为了克服数据融合方法数据融合效果差的问题，提出了一种基于模糊理论的工业物联网数据融合方法。首先划分数据采集区域，采用绝对中值差分法采集数据。其次，根据隶属函数构造模糊集，提取数据属性特征。然后，采用分簇路由协议对可信数据进行筛选，并采用指数平滑法对可信数据进行分类。最后，利用空间和时间相关度分配融合权值，利用模糊理论对工业物联网数据进行融合。实验结果表明，该方法的分类准确率可达99%，数据融合率可达99. 5%，融合时间仅为3. 92 s该方法可以提高数据融合效果。



国家科技图书文献中心  全球文献资源网  京ICP备05055788号-26  机械工业信息研究院 2018-2024