An Intelligent Fusion Algorithm for Uncertain Information Processing

摘要：

　　With the development of various advanced sensors, and some sensing technologies are not mature, so that measurement information was being uncertain, incomplete.This paper adopts an intelligent fusion algorithm with Rough Set for reduction of the attribute set and target set for the raw data from various sensors.Consequently the noise and redundancy will be reduced in sampling.Then constructs information prediction system of SVM according to the preprocessing information structure, and solves the problem of multisensor data fusion in the situation of small sample and uncertainty.In order to get the optimal fusion accuracy, it uses PSO for fusion parameters.To make operation faster and increase the accuracy of the fusion, a feature selection process with PSO is used in this paper to optimize the fusion accuracy by its superiority of optimal search ability.

关键词： Uncertain information Data fusion RS SVM

作者: Peiyi Zhu Benlian Xu Mingli Lu

作者单位: School of Electrical and Automation Engineering,Changshu Institute of technology,Hushan Road, Changshu, Jiangsu

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 293-300

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）