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Title: Research on the kNN-Based Location Algorithm for WLAN Indoor Location Method
Source: International Conference on Engineering and Business Management 2012(Part 5 Innovative Technology) (pp 3430-3433)
Author(s): Chubing Xiao, School of Physics and Technology, Wuhan University, Wuhan, China, 430072
Junyuan Huang, School of Physics and Technology, Wuhan University, Wuhan, China, 430072
Liqiong Wei, Wuhan Changjiang Sub-Branch, Agricultural Bank of China, Wuhan, China, 430019
Abstract: In this paper, we demonstrate a deterministic algorithm-kNN and present the simulation results for the proposed method，especially focus on the relation between sampling point density and positioning accuracy. Numerous results show that the greater density of sampling points, the higher positioning accuracy will be. These findings exhibit great promises to improve the indoor location technology.
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