基于粗糙集和模糊kohonen聚类网络的多传感器数据融合  

Multi-sensor information fusion based on rough set and fuzzy Kohonen clus-tering network

作　　者：刘晖[1] 陈小惠[1] 刘银峰[1] 

机构地区：[1]南京邮电大学自动化学院,南京210003

出　　处：《电子测量与仪器学报》2010年第3期218-223,共6页Journal of Electronic Measurement and Instrumentation

摘　　要：多传感器数据融合的难点在于传感器聚类状态的切换,即在某一时刻该传感器应该往哪个方向融合数据的问题。利用粗糙集进行知识的获取,把54个传感器1天内的可融合的典型聚类分布作为样本空间形成"数据-融合分布"的决策表,然后对一个月的数据根据粗糙集的知识约简方法,去掉冗余的属性和样本。利用模糊kohonen聚类网络进行聚类分析,最后形成传感器数据融合的分布规则.实验证明该模型具有很好的分类效率,可以快速实现传感器聚类分布的判断。The difficulties of fusing Multi-sensor data lie in the switching of the state of sensor clusters.That is,at a given moment which direction the sensor should fuse data into.In this article,first the rough set is used for access of knowledge.The typical clustering distributions of 54 sensors within one day are regarded as sample room for the decision-making table of the ＂data -fusion distribution＂.Next,based on rough set of method of simplified knowledge,for one month date,removed redundant properties and samples.Then,the fuzzy Kohonen clustering network was using to analyze clustering.And finally the patterns of multi-sensor data fusion distribution are formed.The model is proved experimentally to be efficient in classification and rapid in sensor clustering distribution decide.

关 键 词：粗糙集 神经网络 数据融合 传感器网络 TOSSIM 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]