Feature Adaptive Online Sequential Extreme Learning Machine for lifelong indoor localization

doi:10.1007/s00521-014-1714-x

	Feature Adaptive Online Sequential Extreme Learning Machine for lifelong indoor localization
	Jiang, Xinlong 1,2; Liu, Junfa 1; Chen, Yiqiang 1; Liu, Dingjun 3; Gu, Yang 1,2; Chen, Zhenyu 1,2
	2016
发表期刊	NEURAL COMPUTING & APPLICATIONS
ISSN	0941-0643
卷号	27 期号:1 页码:215-225
摘要	Wi-Fi-based indoor localization with high capability and feasibility needs to implement lifelong online learning mechanism. However, the characteristic of Wi-Fi is wide variability, which lies in not only the fluctuation of signal strength value, but also the increase or decrease in the number of access points (APs). The traditional algorithms are effective for signal fluctuation, but cannot handle the dimension-changing problem of features caused by increase and decrease in APs' number. To solve this problem, we propose a Feature Adaptive Online Sequential Extreme Learning Machine (FA-OSELM) algorithm. It can transfer the original model to a new one with a small number of data with new features, so as to make the new model suitable for the new feature dimension. The experiments show that the FA-OSELM can get higher accuracy with a small amount of new data, and it is an effective method to make lifelong indoor localization practical.
关键词	Feature adaptive Online Sequential Extreme Learning Machine (OS-ELM) Lifelong Indoor localization
DOI	10.1007/s00521-014-1714-x
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation of China[61173066] ; Natural Science Foundation of China[41201410] ; Strategic Emerging Industry Development Special Funds of Guangdong Province[2011912030]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000369995700023
出版者	SPRINGER
引用统计	被引频次：34[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/8757
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Jiang, Xinlong
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 3.Xiangtan Univ, Xiangtan 411105, Hunan, Peoples R China
推荐引用方式 GB/T 7714	Jiang, Xinlong,Liu, Junfa,Chen, Yiqiang,et al. Feature Adaptive Online Sequential Extreme Learning Machine for lifelong indoor localization[J]. NEURAL COMPUTING & APPLICATIONS,2016,27(1):215-225.
APA	Jiang, Xinlong,Liu, Junfa,Chen, Yiqiang,Liu, Dingjun,Gu, Yang,&Chen, Zhenyu.(2016).Feature Adaptive Online Sequential Extreme Learning Machine for lifelong indoor localization.NEURAL COMPUTING & APPLICATIONS,27(1),215-225.
MLA	Jiang, Xinlong,et al."Feature Adaptive Online Sequential Extreme Learning Machine for lifelong indoor localization".NEURAL COMPUTING & APPLICATIONS 27.1(2016):215-225.