D-S Theory Based on an Improved PSO for Data Fusion
作者： Peiyi Zhu , Weili Xiong , Ningning Qin , Baoguo Xu
关键词: Robustness (computer science) 、 Sensor fusion 、 Theory based 、 Distance based 、 Computer science 、 Algorithm 、 Particle swarm optimization 、 Simulation test 、 Information fusion 、 Weight value
摘要: The Dempster-Shafer (D-S) theory is an excellent method of information fusion. Because the difference which caused by sensors, it essential to deal with evidence a weighed D-S theory. new data fusion based on improved has been proposed, and set up concept weight sensor itself distance quantification similarity between sets acquire reliability relationship evidences. Considering disadvantages theory, best obtaining value presented particle swarm optimization (PSO). Compared compared methods, this proves more effective advanced making simulation test.
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