Title :
A Multi-Sensor Information Fusion Algorithm based on SVM
Author :
Adu, Jian-hua ; Hu, De-kun ; Peng, Hui ; Tie, Ju-hong
Author_Institution :
Software Dept., Chengdu Univ. of Inf. Technol., Chengdu
Abstract :
Support vector machine is an algorithm based on structural risk minimization, which has good generalization performance. In the course of multi-sensor information fusion of industrial control, sensor has bigger nonlinearity and fuzzy relation between coefficient and relevant parameter. This paper proposed an algorithm of multi-sensor information fusion based on support vector machine, which offered a kind of effective way for modeling process of these little samples, non-linear, high dimension problems.
Keywords :
sensor fusion; support vector machines; SVM; fuzzy relation; industrial control; multisensor information fusion algorithm; structural risk minimization; support vector machine; Electrical equipment industry; Industrial control; Machine learning; Risk management; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Software algorithms; Support vector machine classification; Support vector machines; SVM; information fusion; multi-sensor;
Conference_Titel :
Apperceiving Computing and Intelligence Analysis, 2008. ICACIA 2008. International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3427-5
Electronic_ISBN :
978-1-4244-3426-8
DOI :
10.1109/ICACIA.2008.4769966
