Novel Dynamic KNN with Adaptive Weighting Mechanism for Beacon-based Indoor Positioning System

被引:4
|
作者
Yang, Chong-Yi [1 ]
Ma, Yi-Wei [1 ]
Chen, Jiann-Liang [1 ]
Lin, Chia-Ju [1 ]
Lee, Wei-Lun [1 ]
机构
[1] Natl Taiwan Univ Sci & Technol, Dept Elect Engn, Taipei, Taiwan
来源
JOURNAL OF INTERNET TECHNOLOGY | 2019年 / 20卷 / 05期
关键词
Indoor positioning; Bluetooth Low Energy (BLE); Fingerprinting;
D O I
10.3966/160792642019092005024
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This work proposes a novel dynamic K Nearest Neighbor (KNN) with an adaptive weighting (DKNN-AW) mechanism that performs beacon-based indoor positioning. Four cases are used to prove that DKNN-AW (Dynamic KNN algorithm with Adaptive Weight algorithm) is better than KNN (k-Nearest Neighbors algorithm), KNN-W (KNN with Weight algorithm), DKNN (Dynamic KNN algorithm) and DKNN-W (Dynamic KNN with Weight algorithm). The experimental results demonstrate that, in terms of approximate positioning accuracy, the proposed mechanism outperforms exiting mechanism such as KNN, DKNN, KNN-W and DKNN-W.
引用
收藏
页码:1601 / 1610
页数:10
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