Multisensor Data Fusion Based on Rough Set and ART2 Network

被引：0
|
作者：
Chen, Xiaohui [1 ]
Liu, Hui [1 ]
机构：
[1] Nanjing Univ Posts & Telecommun, Coll Automat, Nanjing 210046, Jiangsu, Peoples R China
来源：
INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS, PTS 1-4 | 2013年 / 241-244卷
关键词：
rough set; neural network; data fusion; sensor net; Tossiom;
D O I：
10.4028/www.scientific.net/AMM.241-244.912
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A difficulty of multisensor data fusion lies in the switching of the state of sensor clusters. That is, which direction should the sensor data been fused into at a given moment? In this paper, firstly, the rough set was used for access of knowledge. The typical clustering distributions of 54 sensors within one day were regarded as sample space for the decision-making table of the "data - fusion distribution". Next, based on the method of knowledge reduction using rough set, the redundant properties and samples of data in one month were removed. Then, the ART2 network was applied for clustering and analyzing, and the distribution rules of multisensor data fusion are formed. The experiment results show that the model is efficient in classification and rapid in sensor clustering distribution decide.
引用
收藏
页码：912 / 915
页数：4
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