A ridgelet kernel approach for regression using particle swarm optimization algorithm

被引：0
|
作者：
Yang, SY [1 ]
Wang, M [1 ]
Jiao, LC [1 ]
机构：
[1] Xidian Univ, Dept Elect Engn, Inst Intelligent Informat Proc, Xian 710071, Peoples R China
来源：
PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), VOLS 1-5 | 2005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：
In this paper, a ridgelet kernel approach is proposed for approximation of multivariate functions, especially those with certain kinds of spatial inhomogeneities. It is based on ridgelet theory, kernel and regularization technology from which we can deduce a regularized kernel regression form. Taking the objective function solved by quadratic programming to define a fitness function, we use particle swarm optimization algorithm to optimize the directions of ridgelets. Experiments in the tasks of regression prove its efficiency.
引用
收藏
页码：2837 / 2842
页数：6
相关论文
共 50 条
  • [21] Blasting vibration parameters using comprehensive regression of wavelet denoising and particle swarm optimization algorithm
    Zhang Le-wen
    Wang Hong-bo
    Quy Dao-hong
    Sun Huai-feng
    Sun Zi-zheng
    Ding Wan-tao
    [J]. ROCK AND SOIL MECHANICS, 2014, 35 : 338 - 342
  • [22] Source Optimization using Particle Swarm Optimization Algorithm in Photolithography
    Wang, Lei
    Li, Sikun
    Wang, Xiangzhao
    Yan, Guanyong
    Yang, Chaoxing
    [J]. OPTICAL MICROLITHOGRAPHY XXVIII, 2015, 9426
  • [23] Automatic kernel clustering with a Multi-Elitist Particle Swarm Optimization Algorithm
    Das, Swagatam
    Abraham, Ajith
    Konar, Amit
    [J]. PATTERN RECOGNITION LETTERS, 2008, 29 (05) : 688 - 699
  • [24] Parameters Optimization of Support Vector Regression Based on Immune Particle Swarm Optimization Algorithm
    Wang, Yan
    Wang, Juexin
    Du, Wei
    Zhang, Chen
    Zhang, Yu
    Zhou, Chunguang
    [J]. WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09), 2009, : 997 - 1000
  • [25] Particle Swarm Optimization Algorithm
    Zhou, Feihong
    Liao, Zizhen
    [J]. SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4, 2013, 303-306 : 1369 - +
  • [26] Optimization of the Particle Swarm Algorithm
    Chytil, J.
    [J]. PIERS 2014 GUANGZHOU: PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM, 2014, : 2355 - 2359
  • [27] Numerical optimization using organizational particle swarm algorithm
    Cong, Lin
    Sha, Yuheng
    Jiao, Licheng
    [J]. SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS, 2006, 4247 : 150 - 157
  • [28] Improved Particle Swarm Optimization using Evolutionary Algorithm
    Chansamorn, Sukanya
    Somgiat, Wichaya
    [J]. 2022 19TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING (JCSSE 2022), 2022,
  • [29] Multiuser detection using the particle swarm optimization algorithm
    Liu, C
    Xiao, Y
    [J]. INTERNATIONAL SYMPOSIUM ON COMMUNICATIONS AND INFORMATION TECHNOLOGIES 2005, VOLS 1 AND 2, PROCEEDINGS, 2005, : 350 - 353
  • [30] Binary wavefront optimization using particle swarm algorithm
    Fang, Longjie
    Zuo, Haoyi
    Yang, Zuogang
    Zhang, Xicheng
    Du, Jinglei
    Pang, Lin
    [J]. LASER PHYSICS, 2018, 28 (07)
12345