A Novel WIFI Indoor Positioning Method Based on Genetic Algorithm and Twin Support Vector Regression

摘要：

　　We propose a novel regression,which is called Twin Support Vector Regression(TSVR)to improve the precision of indoor positioning.Similar as Support Vector Regression(SVR),there are 6 parameters to be identified.However,compared with SVR,less computation time and approximate performance can be achieved with TSVR.Genetic Algorithm(GA)is used to avoid local optimum in indoor positioning to get proper parameters in TSVR.Experimental example is shown to illustrate the effectiveness of the proposed methods.

关键词： TSVR SVR indoor positioning GA

作者: Wenhua Le Zhanbin Wang Jingcheng Wang Guanglei Zhao Haoxuan Miao

作者单位: Department of Automation,Shanghai Jiao Tong University,and Key Laboratory of System Control and Information Processing,Ministry of Education of China,Shanghai 200240

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 4859-4862

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）