Indoor Positioning System Using Artificial Neural Network With Swarm Intelligence

被引：10
|
作者：
Cheng, Chia-Hsin [1 ]
Wang, Tao-Ping [1 ]
Huang, Yung-Fa [2 ]
机构：
[1] Natl Formosa Univ, Dept Elect Engn, Huwei 63201, Yunlin, Taiwan
[2] Chaoyang Univ Technol, Dept Informat & Commun Engn, Taichung 41349, Taiwan
来源：
IEEE ACCESS | 2020年 / 8卷
关键词：
Swarm intelligence; artificial neural network; indoor positioning; QUANTITATIVE-ANALYSIS;
D O I：
10.1109/ACCESS.2020.2990450
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The global positioning system is the most popular outdoor positioning system; however, it is inapplicable to indoor environments. In this study, we created a hybrid algorithm, which applies an artificial neural network to resolve the problems of indoor positioning and a swarm-intelligence algorithm to perform the time-consuming task of adjusting parameters. Experiment results demonstrate that the positioning accuracy of the proposed hybrid algorithm is equivalent to the exhaustive method with search times that are far shorter.
引用
收藏
页码：84248 / 84257
页数：10
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