Based on Rough Sets and Support Vector Machine Application of Multi-sensor Information Fusion Method
Jinxue Xue, Wang Guo-hu, Xiaoqiang Wang, Fengkui Cui · MECS '15 Proceedings of the 2015 International Conference on Mechanical Engineering and Control Systems · 2015
In order to improve the precision and date processing speed of multi-sensor information fusion, a kind of multi-sensor data fusion process algorithm has been studied in this paper. First, based on rough set theory (RS) to attribute reduction the parameter set, we use the advantages of rough set theory in dealing with large amount of data to eliminate redundant information. Then, the data can be trained and classified by Support Vector Machine (SVM). Experimental results showed that this method can improve the speed and accuracy of multi-sensor fusion system.