WiFi Localization Algorithm Based on Snake Optimization Algorithm to Optimize BP Neural Network

被引：1

作者：

Cheng, Kexiong ^{[1
]}

Zhang, Jiawei ^{[1
]}

Tian, Shuangwen ^{[2
]}

Liu, Huan ^{[3
]}

Gong, Jiahua ^{[1
]}

Xie, Yuhao ^{[4
]}

机构：

[1] Chengdu Univ Technol, Sch Nucl Technol & Automat Engn, Chengdu 610059, Peoples R China

[2] Inner Mongolia North Heavy Ind Grp Co Ltd, Equipment Res Inst, Baotou 010000, Inner Mongolia, Peoples R China

[3] Sichuan Anxin Kechuang Technol Co Ltd, Chengdu 610045, Peoples R China

[4] Chengdu Univ Technol, Sch Comp Sci & Cyber Secur, Oxford Brookes Coll, Chengdu 610059, Sichuan, Peoples R China

来源：

2022 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, COMPUTER VISION AND MACHINE LEARNING (ICICML) | 2022年

关键词：

Snake Optimization; BP neural network; Indoor positioning; WiFi;

D O I：

10.1109/ICICML57342.2022.10009784

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 hottest area of indoor localization technology research right now is WiFi localization. This research provides a prediction model based on BP neural network, with the model's weights and thresholds tuned using snake optimization technique, for the demand of WiFi location fingerprint indoor localization technology. The issues that BP neural network has with easy local optimum attainment, slow convergence, and weak interference immunity are resolved. The simulation is used to confirm the viability and efficiency of the indoor WiFi localization technology method.

引用

页码：615 / 618

页数：4

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