A particle swarm and chaos combination approach for vehicle simulator optimization

被引：0
|
作者：
Zhao, Qiang [1 ]
Gao, Fang [2 ]
机构：
[1] NE Forestry Univ, Sch Traff Transportat Engn, Harbin 150040, Peoples R China
[2] Harblin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China
来源：
ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 2 | 2006年
关键词：
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：
Mechanism design is one crucial step in vehicle simulator developing. A combined approach of particle swarm optimization (PSO) algorithm and mutative scale chaos search algorithm is proposed for the parameters optimization of motion mechanism of vehicle simulator. The PSO algorithm is run to get the global best particle as the candidate solution, and then mutative scale chaos search iterations are employed to improve the local search ability. This combined search approach can solve the invalidation problem of chaos optimization algorithm in a large scale searching, meanwhile it can improve local search precision of PSO. This approach is successfully used in design of a vehicle simulator.
引用
收藏
页码：986 / +
页数：2
相关论文
共 50 条
  • [11] A Combination of Genetic Algorithm and Particle Swarm Optimization for Vehicle Routing Problem with Time Windows
    Xu, Sheng-Hua
    Liu, Ji-Ping
    Zhang, Fu-Hao
    Wang, Liang
    Sun, Li-Jian
    SENSORS, 2015, 15 (09) : 21033 - 21053
  • [12] The Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation
    Mengxia, L.
    Ruiquan, L.
    Yong, D.
    INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2016, 11 (06) : 804 - 818
  • [13] Chaos Cultural Particle Swarm Optimization and Its Application
    Wang, Ying
    Zhou, Jianzhong
    Lu, Youlin
    Qin, Hui
    Zhang, Yongchuan
    ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 3, PROCEEDINGS, 2009, 5553 : 30 - 40
  • [14] Modified Quantum Particle Swarm Optimization for Chaos Synchronization
    Ko, Chia-Nan
    Lee, Ching-I
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB 2016), 2016, : 48 - 51
  • [15] Method of particle swarm optimization based on the chaos map
    Liu D.-H.
    Yuan S.-C.
    Lan Y.
    Ma X.-J.
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2010, 37 (04): : 764 - 769
  • [16] Chaos-enhanced accelerated particle swarm optimization
    Gandomi, Amir Hossein
    Yun, Gun Jin
    Yang, Xin-She
    Talatahari, Siamak
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2013, 18 (02) : 327 - 340
  • [17] An Improved Particle Swarm Optimization Method Based on Chaos
    Yang, Zuyuan
    Yang, Huafen
    Yang, You
    Zhang, Lihui
    2014 10TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2014, : 209 - 213
  • [18] Mutative scale chaos particle swarm optimization algorithm
    Wang, Hong-gang
    Ma, Liang
    Zhang, Hui-zhen
    Li, Gao-ya
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON SYSTEM MANAGEMENT, 2008, : 71 - 77
  • [19] CAPSO: Chaos Adaptive Particle Swarm Optimization Algorithm
    Duan, Youxiang
    Chen, Ning
    Chang, Lunjie
    Ni, Yongjing
    Kumar, S. V. N. Santhosh
    Zhang, Peiying
    IEEE ACCESS, 2022, 10 : 29393 - 29405
  • [20] Chaos particle swarm optimization with Eensemble of chaotic systems
    Pluhacek, Michal
    Senkerik, Roman
    Davendra, Donald
    SWARM AND EVOLUTIONARY COMPUTATION, 2015, 25 : 29 - 35
12345