Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (9): 1434-1442.doi: 10.23940/ijpe.20.09.p12.14341442

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Wireless Sensor Node Location based on IGWO-LSSVM

Yong Yang*   

  1. Zhejiang Industry Polytechnic College, Shaoxing, 312000, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: * E-mail address:
  • About author:Yong Yang is a Senior engineer at Zhejiang Industry Polytechnic College, He received her master degree from Hangzhou Dianzi University,his research directions is research on wireless sensing.

Abstract: In view of the low node accuracy in wireless sensor node positioning, this paper proposes a node positioning algorithm based on the Improved Grey Wolf Optimization and Least Squares Support Vector Machine (IGWO-LSSVM). First, a wireless sensor positioning model in two-dimensional space is established. Then, the least squares support vector machine is used to model and locate unknown nodes. Finally, the least square vector machine parameters are optimized based on chaos mapping, adaptive factors, and the golden sine gray wolf algorithm to obtain node positioning. Simulation experiments show that compared with other algorithms, this algorithm has a better effect on the accuracy of node positioning.

Key words: gray wolf algorithm, node positioning, golden sine, least squares support vector machine