Application Study of Data Fusion Using Rough Set and Neural Network
Xiaohong Chen · Computer Technology and Development · 2013
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.First the rough set is used for acquisition 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,remove redundant properties and samples.Then,the neural network is used 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 decision.