A wireless sensor network localization algorithm based on particle swarm optimization aided least square support vector machine

被引：0

作者：

Ji, Feng ^{[1
]}

Tian, Jun ^{[1
]}

Xu, Yuqi ^{[1
]}

Rong, Hao ^{[2
]}

Mug, Xiaoyang ^{[2
]}

Wang, Youming ^{[2
]}

机构：

[1] Shaanxi Environm Protect Res Inst, Xian 710100, Shaanxi, Peoples R China

[2] Xian Univ Posts & Telecommun, Xian 710121, Shaanxi, Peoples R China

来源：

PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019) | 2019年

基金：

中国国家自然科学基金;

关键词：

particle swarm optimization; least square support vector machine; wireless sensor network; localization; INTERNET; THINGS;

D O I：

10.1109/itnec.2019.8729451

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 paper is focused on the localization problems of scattered nodes in the traditional wireless sensor network. A node localization method based on particle swarm optimization aided least square support vector regression is proposed. Firstly, the nearest neighbor clustering algorithm is used to determine the data type, where the nodes closest to the unknown node are employed as the clustering center. Then, a distributed structure based on the meshing of wireless sensor network is presented. Finally, the particle swarm optimization aided least square support vector machine algorithm is proposed for the wireless sensor network localization. Numerical experiments show that the proposed method is accurate and effective in wireless sensor network localization problems.

引用

页码：2290 / 2293

页数：4

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