Earticle

초록

영어

This paper proposed an improved particle swarm optimization positioning algorithm based on virtual force-directed method for node localization of wireless sensor networks. The improved algorithm adopted adaptive inertia weight and adaptive mutation operation on global optimum, which overcomes the disadvantage of traditional particle swarm optimization algorithm that is easy to be trapped in local optimum. Fast convergence to near optimal solutions can be achieved after inertia weight is adjusted to be bigger, and smaller inertia weight can result in high precision solution. Through adaptive mutation on the global optimum, the improved algorithm can jump out of the current search area to maximize the coverage of the network nodes and the convergence speed. Compared with the virtual force-directed particle swarm optimization algorithm, the simulation results indicate that the improved algorithm has the advantages of faster convergence speed, lower energy consumption, higher precision and better stability.

목차

Abstract
 1. Introduction
 2. Virtual Force-Directed Particle Swarm Optimization Algorithm
  2.1. Virtual Force Algorithm
  2.2. Particle Swarm Optimization Algorithm
  2.3. The combination of virtual force algorithm and PSO
 3. Improved Algorithm Based on Adaptive
  3.1. Adaptive Inertia Weight
  3.2. Adaptive Mutation Operation on Global Optimum Position
 4. Simulation
 5. Conclusion
 References

키워드

저자

• Jiachen Ma [ School of Astronautics, Harbin Institute of Technology, Harbin 150001, China ]
• Qiang Liu [ School of Astronautics, Harbin Institute of Technology, Harbin 150001, China ]
• Wei Xie [ School of Astronautics, Harbin Institute of Technology, Harbin 150001, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605