Ensemble algorithm of neural networks and its application

被引:0
|
作者
Liu, Y [1 ]
Wang, Y [1 ]
Zhang, BF [1 ]
Wu, GF [1 ]
机构
[1] Shanghai Univ, Sch Engn & Comp Sci, Shanghai 200072, Peoples R China
关键词
neural network ensemble; RBF neural network; genetic algorithm;
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
Neural network ensemble is a very hot topic in both neural networks and machine learning communities [1]. In this paper, a new approach named BAGAEN is proposed, in which adaptive genetic. algorithm and Bootstrap algorithm are employed to increase the different degrees among individual RBF neural networks in order to enhance the generalization ability of a neural network system. The training set for individual RBF neural network is generated by the algorithm based on Bootstrap and the result can be obtained by using majority voting method or simple averaging method. Experimental results show that BAGAEN has preferable. performance in generating ensembles with strong generalization ability. Finally, BAGAEN is applied to predict the magnitude of earthquake.
引用
收藏
页码:3464 / 3467
页数:4
相关论文
共 50 条
  • [31] Bayesian Neural Networks and Its Application
    Fan, Chunling
    Gao, Feng
    Sun, Sitong
    Cui, Fengying
    ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 3, PROCEEDINGS, 2008, : 446 - 450
  • [32] THE APPLICATION OF A GENETIC APPROACH AS AN ALGORITHM FOR NEURAL NETWORKS
    HEISTERMANN, J
    LECTURE NOTES IN COMPUTER SCIENCE, 1991, 496 : 297 - 301
  • [33] Discrete process neural networks algorithm with application
    Yang, S. (yangshuyun68@126.com), 1600, Binary Information Press, Flat F 8th Floor, Block 3, Tanner Garden, 18 Tanner Road, Hong Kong (11):
  • [34] The Algorithm and Application of Quantum Wavelet Neural Networks
    Liu, Kai
    Peng, Li
    Yang, Qin
    2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5, 2010, : 2941 - 2945
  • [35] Stochastic resonance in an ensemble of single-electron neuromorphic devices and its application to competitive neural networks
    Oya, Takahide
    Asai, Tetsuya
    Amemiya, Yoshihito
    CHAOS SOLITONS & FRACTALS, 2007, 32 (02) : 855 - 861
  • [36] Ensemble Stochastic Configuration Networks for Estimating Prediction Intervals: A Simultaneous Robust Training Algorithm and Its Application
    Lu, Jun
    Ding, Jinliang
    Dai, Xuewu
    Chai, Tianyou
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (12) : 5426 - 5440
  • [37] Evolutionary algorithm of radial basis function neural networks and its application in face recognition
    Li, Jianyu
    Huang, Xianglin
    Li, Rui
    Yang, Shuzhong
    Qi, Yingjian
    INTELLIGENT INFORMATION PROCESSING AND WEB MINING, PROCEEDINGS, 2006, : 65 - +
  • [38] Improvements to FP algorithm in feedforward neural networks and its application in noisy character recognition
    Zhao, YN
    Liu, D
    Sun, FJ
    CHINESE JOURNAL OF ELECTRONICS, 2000, 9 (04): : 393 - 396
  • [39] Neural network ensemble based on general entropy and its application
    Lin Jian
    Zhu Bangzhu
    ICCSE'2006: Proceedings of the First International Conference on Computer Science & Education: ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION, 2006, : 807 - 810
  • [40] Ensemble of deep capsule neural networks: an application to pediatric pneumonia prediction
    Bodapati, Jyostna Devi
    Rohith, V. N.
    Dondeti, Venkatesulu
    PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE, 2022, 45 (3) : 949 - 959