AN IMPROVED ADAPTIVE PROPAGATION CHAOTIC PARTICLE SWARM OPTIMIZATION ALGORITHM BASED ON IMMUNE SELECTION

被引：0
|
作者：
Huang, Ke [1 ]
Zhang, Haolan [1 ]
Wang, Yiwen [1 ]
Yu, Changbin [1 ]
机构：
[1] Zhejiang Univ, Ningbo Inst Technol, Ningbo 315100, Zhejiang, Peoples R China
来源：
PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 1 | 2017年
关键词：
Particle swarm optimization algorithm; Immune selection; Adaptive propagation; Multi-population evolution; Traffic network optimization; MODEL;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The particle swarm optimization algorithm is improved by introducing the immune selection, adaptive propagation, multi-population evolution. An improved adaptive propagation chaotic particle swarm optimization algorithm based on immune selection (IS-APCPSO algorithm for short) is proposed in this paper. The performance of several algorithms has been compared by a classic example of traffic network optimization. It is proved that the improved algorithm in accelerating convergence rate, increasing the diversity of particles, and preventing premature phenomenon is effective. The novel algorithm is expected to be used in the model solution of large-scale complex traffic network optimization problem.
引用
收藏
页码：105 / 110
页数：6
相关论文
共 50 条
  • [21] An Algorithm Based on the Improved Particle Swarm Optimization
    Ge, Ri-Bo
    [J]. PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, KNOWLEDGE ENGINEERING AND INFORMATION ENGINEERING (SEKEIE 2014), 2014, 114 : 176 - 179
  • [22] Chaotic synchronization of adaptive inverse control based on hybrid particle swarm optimization algorithm
    Liu, Wei
    Duan, Yubo
    Shao, Keyong
    Wang, Kejun
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS I-V, CONFERENCE PROCEEDINGS, 2007, : 2409 - 2413
  • [23] PARAMETER ESTIMATION FOR NOISY CHAOTIC SYSTEMS BASED ON AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM
    Wei, Jiamin
    Yu, Yongguang
    Wang, Sha
    [J]. JOURNAL OF APPLIED ANALYSIS AND COMPUTATION, 2015, 5 (02): : 232 - 242
  • [24] Satellite navigation satellite selection algorithm based on improved particle swarm optimization
    Wang, Ershen
    Sun, Caimiao
    Huang, Yufeng
    Li, Xuan
    Bie, Yuxia
    Qu, Pingping
    [J]. Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2021, 47 (01): : 1 - 6
  • [25] Multi-objective adaptive chaotic particle swarm optimization algorithm
    Yang, Jing-Ming
    Ma, Ming-Ming
    Che, Hai-Jun
    Xu, De-Shu
    Guo, Qiu-Chen
    [J]. Kongzhi yu Juece/Control and Decision, 2015, 30 (12): : 2168 - 2174
  • [26] An improved threshold selection algorithm based on particle swarm optimization for image segmentation
    Wei, Kaiping
    Zhang, Tao
    Shen, Xianjun
    Liu, Jingnan
    [J]. ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 5, PROCEEDINGS, 2007, : 591 - +
  • [27] Adaptive Virtual Machine Scheduling Algorithm Based on Improved Particle Swarm Optimization
    Wei, Chuanj Iang
    Zhuang, Yi
    [J]. PROCEEDINGS OF 2019 IEEE 10TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2019), 2019, : 328 - 334
  • [28] Research on Improved Adaptive Chaos Optimization Particle Swarm Optimization Algorithm
    Qi Changxing
    Bi Yiming
    Han Huihua
    Li Yong
    Zhai Shimei
    [J]. PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON ROBOTICS AND ARTIFICIAL INTELLIGENCE (ICRAI 2017), 2015, : 15 - 19
  • [29] Adaptive Vaccine Extraction Immune Particle Swarm Optimization Algorithm
    Man Chun-tao
    Sheng Gui-min
    Zhang Tao
    [J]. PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOLS 1-4, 2009, : 1626 - +
  • [30] An Improved Particle Swarm Optimization Algorithm with Adaptive Inertia Weights
    Li, Mi
    Chen, Huan
    Wang, Xiaodong
    Zhong, Ning
    Lu, Shengfu
    [J]. INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2019, 18 (03) : 833 - 866
12345