An enhanced fuzzy neural network

被引：0
|
作者：
Kim, KB
Joo, YH
Cho, JH
机构：
[1] Kunsan Natl Univ, Sch Elect & Informat Engn, Kunsan, South Korea
[2] Catholic Univ Pusan, Dept Comp Informat, Pusan, South Korea
来源：
PARALLEL AND DISTRIBUTED COMPUTING: APPLICATIONS AND TECHNOLOGIES, PROCEEDINGS | 2004年 / 3320卷
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we propose a novel approach for evolving the architecture of a multi-layer neural network. Our method uses combined ART1 algorithm and Max-Min neural network to self-generate nodes in the hidden layer. We have applied the proposed method to the problem of recognizing ID number in identity cards. Experimental results with a real database show that the proposed method has better performance than a conventional neural network.
引用
收藏
页码：176 / 179
页数：4
相关论文
共 50 条
  • [1] An Enhanced Online Self-organizing Fuzzy Neural Network
    San, L.
    Er, M. J.
    Li, X.
    Zhai, L. Y.
    Torabi, A. J.
    11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV 2010), 2010, : 2214 - 2220
  • [2] Enhanced multivariable TS fuzzy modeling in neural network perspective
    Ciftcioglu, Ö
    Sariyildiz, IS
    NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society, 2005, : 150 - 155
  • [3] An enhanced fuzzy neuron controller for curved search neural network learning
    Wu, PT
    Fang, SC
    Nuttle, HLW
    IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL VI, 2000, : 535 - 540
  • [4] An Enhanced Fuzzy Min-Max Neural Network for Pattern Classification
    Mohammed, Mohammed Falah
    Lim, Chee Peng
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (03) : 417 - 429
  • [5] An enhanced discriminability recurrent fuzzy neural network for temporal classification problems
    Wu, Gin-Der
    Zhu, Zhen-Wei
    FUZZY SETS AND SYSTEMS, 2014, 237 : 47 - 62
  • [6] Evolutionary identification of a recurrent fuzzy neural network with enhanced memory capabilities
    Stavrakoudis, D. G.
    Papastamoulis, A. K.
    Theocharis, J. B.
    2008 3RD INTERNATIONAL WORKSHOP ON GENETIC AND EVOLVING FUZZY SYSTEMS, 2008, : 75 - 80
  • [7] An Enhanced General Fuzzy Min-Max Neural Network For Classification
    Donglikar, Neha V.
    Waghmare, Jaishri M.
    2017 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS), 2017, : 757 - 764
  • [8] Enhanced Fuzzy-Relational Neural Network with Alternative Relational Products
    Mendoza-Castaneda, Efrain
    Reyes-Garcia, Carlos A.
    Jair Escalante, Hugo
    Moreno, Wilfrido
    Rosales-Perez, Alejandro
    PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014, 2014, 8827 : 666 - 673
  • [9] A novel fuzzy neural network: The vague neural network
    Fang, R
    Zhao, YB
    Li, WS
    ICCI 2005: Fourth IEEE International Conference on Cognitive Informatics - Proceedings, 2005, : 94 - 99
  • [10] A flexible enhanced fuzzy min-max neural network for pattern classification
    Alhroob, Essam
    Mohammed, Mohammed Falah
    Al Sayaydeh, Osama Nayel
    Hujainah, Fadhl
    Ghani, Ngahzaifa Ab
    Lim, Chee Peng
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 251
12345