Hybrid SVR-PSO for identification of nonlinear system

被引：0
|
作者：
机构：
[1] Wang, Xianfang
[2] Du, Zhiyong
[3] Shen, Yi-Xian
来源：
| 2013年 / CESER Publications, Post Box No. 113, Roorkee, 247667, India卷 / 49期
基金：
中国国家自然科学基金;
关键词：
Particle swarm optimization (PSO);
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper develops a hybrid support vector regression (SVR)-particle swarm optimization (PSO) model to identify nonlinear systems. The predictive accuracy of SVR models is highly dependent on their learning parameters. Therefore, PSO is exploited to seek the optimal hyper-parameters for SVR in order to improve its generalization capability. The proposed identification procedure is successfully applied to measurements of nonlinear systems. The efficiency of the proposed algorithm was demonstrated by some simulation examples. © 2013 by CESER Publications.
引用
收藏
相关论文
共 50 条
  • [41] A CSI 300 Index Prediction Model Based on PSO-SVR-GRNN Hybrid Method
    Chen J.
    Yang H.
    Mobile Information Systems, 2022, 2022
  • [42] SISO nonlinear system identification using a fuzzy-neural hybrid system
    Lin, CJ
    INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 1997, 8 (03) : 325 - 337
  • [43] Study on PSO for the optimization of SVR parameters selection
    Xiong Wei-li
    Xu Bao-guo
    PROCEEDINGS OF THE 2007 CHINESE CONTROL AND DECISION CONFERENCE, 2007, : 447 - +
  • [44] H-PSO-LSTM: Hybrid LSTM Trained by PSO for Online Handwriter Identification
    Moalla, Hounaida
    Elloumi, Walid
    Alimi, Adel M.
    NEURAL INFORMATION PROCESSING (ICONIP 2017), PT IV, 2017, 10637 : 41 - 50
  • [45] Investigating the Slurry Fluidity and Strength Characteristics of Cemented Backfill and Strength Prediction Models by Developing Hybrid GA-SVR and PSO-SVR
    Du, Kun
    Liu, Minghui
    Zhou, Jian
    Khandelwal, Manoj
    MINING METALLURGY & EXPLORATION, 2022, 39 (02) : 433 - 452
  • [46] Investigating the Slurry Fluidity and Strength Characteristics of Cemented Backfill and Strength Prediction Models by Developing Hybrid GA-SVR and PSO-SVR
    Kun Du
    Minghui Liu
    Jian Zhou
    Manoj Khandelwal
    Mining, Metallurgy & Exploration, 2022, 39 : 433 - 452
  • [47] Robust Optimization of Occupant Restraint System Based on PSO-SVR Approximation Model
    Zhang H.
    Hu S.
    Zhou D.
    Gao J.
    Gu X.
    Gu, Xianguang (gxghfut@163.com), 2020, SAE-China (42): : 462 - 467
  • [48] Predictive Analytics for Octane Number: A Novel Hybrid Approach of KPCA and GS-PSO-SVR Model
    Li, Baosheng
    Qin, Chuandong
    IEEE ACCESS, 2021, 9 : 66531 - 66541
  • [49] Research on a nonlinear hybrid optimal PSO microseismic positioning method
    Xiao, Yang
    Liu, Wei-jian
    Wang, Hao-nan
    Hou, Meng-jie
    Dong, Sen-sen
    Zhang, Zhi-zeng
    APPLIED GEOPHYSICS, 2024,
  • [50] Modeling and identification of a nonlinear hybrid dynamical system in batch fermentation of glycerol
    Wang, Juan
    Ye, Jianxiong
    Feng, Enmin
    Yin, Hongchao
    Xiu, Zhilong
    MATHEMATICAL AND COMPUTER MODELLING, 2011, 54 (1-2) : 618 - 624
12345