A kind of adaptive genetic algorithm and it's application in model identification

被引：0
|
作者：
Liu, CL [1 ]
Wang, ZY [1 ]
Bao, Z [1 ]
机构：
[1] N China Elect Power Univ, Fac Automat, Baoding 071003, Peoples R China
来源：
Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9 | 2005年
关键词：
model identification; adaptive genetic algorithms; ARX model; float-encoding;
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：
In this paper, a kind of adaptive genetic algorithm based on float-encoding is introduced and applied in system identification. In the algorithm, the cross probability and mutation probability are assigned to each gene according to the fitness adaptively. The improvement can guarantee the colony multiplicity and the convergence. The simulation results of identifying a theoretical model and application to a real object have proved the accuracy and robust of adaptive genetic algorithm.
引用
收藏
页码：2865 / 2869
页数：5
相关论文
共 50 条
  • [31] Adaptive population disappear of genetic algorithm and its application
    Chen, TG
    Wang, YH
    [J]. 2004 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL ELECTROMAGNETICS AND ITS APPLICATIONS, PROCEEDINGS, 2004, : 145 - 148
  • [32] Adaptive genetic algorithm and its application to the Riccati equation
    Hao, xiaohong
    Fan, Bo
    [J]. Lanzhou Daxue Xuebao/Journal of Lanzhou University, 2000, 36 (01): : 39 - 43
  • [33] Analysis of Norms in Adaptive Algorithm on Application of System Identification
    Panda, Sarthak
    Mohanty, Mihir Narayan
    [J]. INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 1, INDIA 2016, 2016, 433 : 579 - 588
  • [34] Application of modified Stribeck model and simulated annealing genetic algorithm in friction parameter identification
    Guo, Haichen
    Yang, Pingping
    Zhou, Boyan
    Gu, Xincheng
    [J]. 2017 12TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (IEEE ISKE), 2017,
  • [35] Application of neural network and genetic algorithm in identification of a model of a variable mass underwater vehicle
    Shafiei, M. H.
    Binazadeh, T.
    [J]. OCEAN ENGINEERING, 2015, 96 : 173 - 180
  • [36] Application of multiple-population genetic algorithm in parameter identification for PBX constitutive model
    Gao J.
    Huang Z.
    [J]. 2016, Explosion and Shock Waves (36): : 861 - 868
  • [37] An expanded T-S model identification based on quantum genetic algorithm
    [J]. Li, H. (hblh198095@163.com), 1600, Northeast University (28):
  • [38] Ship Model Identification with Genetic Algorithm Tuning
    Miller, Anna
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (12):
  • [39] Parameters Identification of Short Hanger Based on Adaptive Genetic Algorithm
    Yuan, Pei
    [J]. PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON BIOLOGICAL SCIENCES AND TECHNOLOGY, 2016, : 131 - 135
  • [40] Adaptive Genetic Algorithm Evidence Model and Its Application for Discriminating Enemy Radar Operation Intention
    Pan Wei
    Li Wenjun
    Yang Jinsong
    [J]. PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2012, : 1088 - 1093
12345