计算机工程与应用2016，Vol.52Issue(6)：90-93,4.DOI:10.3778/j.issn.1002-8331.1404-0106
基于改进支持向量机的Wi-Fi室内定位算法
Wi-Fi indoor localization algorithm based on improved support vector machine
摘要
Abstract
Wi-Fi signal is unstable in complex indoor environment and localization precision of support vector machine is very low. In order to improve the localization precision of indoor nodes, a novel indoor localization algorithm is proposed based on improved support vector machine. The kernel principal component analysis is used to extract useful information and obtain the features which reduce the computing complexity, and then support vector machine is used to construct non-linear mapping localization model between features and physical location, in which parameters are optimized by particle swarm optimization algorithm. The simulation experiments are used to test the performance. The results show that the pro-posed algorithm has improved localization precision and efficiency for indoor localization.关键词
室内定位/支持向量机/核主成分分析/粒子群优化算法Key words
indoor localization/support vector machine/kernel principal component analysis/particle swarm optimiza-tion algorithm分类
信息技术与安全科学引用本文复制引用
丁雪芳,王琪..基于改进支持向量机的Wi-Fi室内定位算法[J].计算机工程与应用,2016,52(6):90-93,4.基金项目
陕西省教育厅项目（No.20130031312）。 （）
