A Quantum Behaved Particle Swarm Optimization with a Chaotic Operator

被引：0
作者：
Li, Mingming [1 ]
Cao, Dandan [1 ,2 ]
Gao, Hao [3 ]
机构：
[1] Beijing Inst Control Engn, Beijing, Peoples R China
[2] China Acad Space Technol, Hangzhou Inst, Hangzhou, Peoples R China
[3] Nanjing Univ Posts & Commun, Nanjing, Peoples R China
来源：
ARTIFICIAL INTELLIGENCE AND ROBOTICS, ISAIR 2023 | 2024年 / 1998卷
关键词：
quantum behaved; particle swarm optimization; chaotic operator; ARTIFICIAL BEE COLONY; ALGORITHM;
D O I：
10.1007/978-981-99-9109-9_21
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
As a popular population based Evolutionary Algorithm, quantum behaved particle swarm optimization (QPSO) has applied widely in many real-world problems. In this paper, for further enhancing the performance of QPSO, we proposed a popular chaotic map into it. The new chaotic operator not only accelerate the convergence rate but also strengthen the search ability in the total space of the original QPSO. Furthermore, we verify the revised algorithm on some traditional benchmark functions. The final compared results on the images prove the superior of our algorithm.
引用
收藏
页码：212 / 218
页数：7
相关论文
共 18 条
  • [1] Optimized control for medical image segmentation: improved multi-agent systems agreements using Particle Swarm Optimization
    Allioui, Hanane
    Sadgal, Mohamed
    Elfazziki, Aziz
    [J]. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 12 (09) : 8867 - 8885
  • [2] Particle Swarm Optimization Algorithm with Mutation Operator for Particle Filter Noise Reduction in Mechanical Fault Diagnosis
    Chen, Hanxin
    Fan, Dong Liang
    Fang, Lu
    Huang, Wenjian
    Huang, Jinmin
    Cao, Chenghao
    Yang, Liu
    He, Yibin
    Zeng, Li
    [J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2020, 34 (10)
  • [3] Gaussian Artificial Bee Colony Algorithm Approach Applied to Loney's Solenoid Benchmark Problem
    Coelho, Leandro dos Santos
    Alotto, Piergiorgio
    [J]. IEEE TRANSACTIONS ON MAGNETICS, 2011, 47 (05) : 1326 - 1329
  • [4] An efficient particle swarm approach for mixed-integer programming in reliability-redundancy optimization applications
    Coelho, Leandro dos Santos
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2009, 94 (04) : 830 - 837
  • [5] An Improved Artificial Bee Colony Algorithm With its Application
    Gao, Hao
    Shi, Yujiao
    Pun, Chi-Man
    Kwong, Sam
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (04) : 1853 - 1865
  • [6] Real-Time Detection of Moving Magnetic Target Using Distributed Scalar Sensor Based on Hybrid Algorithm of Particle Swarm Optimization and Gauss-Newton Method
    Ge, Jian
    Wang, Shuqiao
    Dong, Haobin
    Liu, Huan
    Zhou, Dan
    Wu, Shuang
    Luo, Wang
    Zhu, Jun
    Yuan, Zhiwen
    Zhang, Haiyang
    [J]. IEEE SENSORS JOURNAL, 2020, 20 (18) : 10717 - 10723
  • [7] Karaboga D., 2005, TR06 ERC U COMP ENG
  • [8] Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
  • [9] Hybrid differential evolution with artificial bee colony and its application for design of a reconfigurable antenna array with discrete phase shifters
    Li, X.
    Yin, M.
    [J]. IET MICROWAVES ANTENNAS & PROPAGATION, 2012, 6 (14) : 1573 - 1582
  • [10] Lorenz E. N., 1993, The Essence of Chaos, P181
12