Target Position Measurement Technology Based on Quantum-behaved Particle Swarm Optimization

被引：1
|
作者：
Yao, Jinjie [1 ]
Yang, Jing [1 ]
Li, Jian [1 ]
Wang, Liming [2 ]
Han, Yan [2 ]
机构：
[1] North Univ China, Natl Key Lab Elect Testing Technol, Taiyuan 030051, Peoples R China
[2] North Univ China, Minist Educ, Instrumentat Sci & Dynam Testing Lab, Taiyuan 030051, Peoples R China
来源：
SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4 | 2013年 / 303-306卷
关键词：
Particle swarm; Quantum behavior; Target localization; Time difference of arrival; LOCALIZATION; ALGORITHM;
D O I：
10.4028/www.scientific.net/AMM.303-306.403
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Quantum-behaved particle swarm optimization algorithm (QPSO) was proposed as a kind of swarm intelligence, which outperformed standard particle swarm optimization algorithm (PSO) in search ability. This paper presents an improved QPSO with nonlinear controlled parameter according to the fitness value of the particles. Simultaneously, we apply the improved QPSO to solve the problems of target position measurement. The experimental results show that the improved QPSO has faster convergence speed, higher measurement accuracy, and good localization performance.
引用
收藏
页码：403 / +
页数：2
相关论文
共 50 条
  • [1] Quantum-behaved particle swarm optimization based on solitons
    Saeed Fallahi
    Mohamadreza Taghadosi
    [J]. Scientific Reports, 12
  • [2] Quantum-behaved particle swarm optimization based on solitons
    Fallahi, Saeed
    Taghadosi, Mohamadreza
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [3] Quantum-behaved particle swarm optimization with elitist mean best position
    Xi, Maolong
    Sun, Jun
    Xu, Wenbo
    [J]. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2007, 14 : 1643 - 1647
  • [4] Parallel quantum-behaved particle swarm optimization
    Tian, Na
    Lai, Choi-Hong
    [J]. INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2014, 5 (02) : 309 - 318
  • [5] A modified Quantum-behaved Particle Swarm Optimization
    Sun, Jun
    Lai, C. -H.
    Xu, Wenbo
    Ding, Yanrui
    Chai, Zhilei
    [J]. COMPUTATIONAL SCIENCE - ICCS 2007, PT 1, PROCEEDINGS, 2007, 4487 : 294 - +
  • [6] A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization
    Sun, Tao
    Xu, Ming-hai
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2017, 2017
  • [7] Parallel quantum-behaved particle swarm optimization
    Na Tian
    Choi-Hong Lai
    [J]. International Journal of Machine Learning and Cybernetics, 2014, 5 : 309 - 318
  • [8] A Review of Quantum-behaved Particle Swarm Optimization
    Fang, Wei
    Sun, Jun
    Ding, Yanrui
    Wu, Xiaojun
    Xu, Wenbo
    [J]. IETE TECHNICAL REVIEW, 2010, 27 (04) : 336 - 348
  • [9] Quantum-Behaved Particle Swarm Optimization Based on Comprehensive Learning
    Long, HaiXia
    Zhang, XiuHong
    [J]. ADVANCES IN ELECTRONIC COMMERCE, WEB APPLICATION AND COMMUNICATION, VOL 2, 2012, 149 : 15 - 20
  • [10] Dynamic clustering based on quantum-behaved particle swarm optimization
    Fu, Liuqiang
    Zhang, Hongwei
    [J]. ADVANCES IN APPLIED SCIENCE AND INDUSTRIAL TECHNOLOGY, PTS 1 AND 2, 2013, 798-799 : 808 - 813
12345