Backpropagation Learning Method with Interval Type-2 Fuzzy Weights in Neural Networks

被引:0
作者
Gaxiola, Fernando [1 ]
Melin, Patricia [1 ]
Valdez, Fevrier [1 ]
Castillo, Oscar [1 ]
机构
[1] Tijuana Inst Technol, Tijuana, Mexico
来源
2013 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2013年
关键词
Neural Networks; Type-2 Fuzzy Weights; Backpropagation Algorithm; Type-2 fuzzy system; ALGORITHM; SYSTEMS; LOGIC; OPTIMIZATION; DESIGN;
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 neural network learning method with lower and upper type-2 fuzzy weight adjustment is proposed. The general mathematical analysis of the proposed learning method architecture and the adaptation of the interval type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that manage weight adaptation and especially type-2 fuzzy weights. In this paper the neural network architecture managing lower and upper type-2 fuzzy weights and the obtained lower and upper final results are presented. The proposed approach is applied to a case of Mackey-Glass time series prediction.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] A Fast Method for Computing the Centroid of a Type-2 Fuzzy Set
    Wu, Hsin-Jung
    Su, Yao-Lung
    Lee, Shie-Jue
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2012, 42 (03): : 764 - 777
  • [32] An Interval Type-2 Fuzzy System with Hybrid Intelligent Learning
    Meesad, Phayung
    2014 4TH WORLD CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGIES (WICT), 2014, : 263 - 268
  • [33] Generalized Type-2 Fuzzy Systems for controlling a mobile robot and a performance comparison with Interval Type-2 and Type-1 Fuzzy Systems
    Sanchez, Mauricio A.
    Castillo, Oscar
    Castro, Juan R.
    EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (14) : 5904 - 5914
  • [34] An Optimal Defuzzification Method for Interval Type-2 Fuzzy Logic Control Scheme
    Allawi, Ziyad T.
    Abdalla, Turki Y.
    2015 SCIENCE AND INFORMATION CONFERENCE (SAI), 2015, : 619 - 627
  • [35] Interval Type-2 Fuzzy Clustering Based Association Rule Mining Method
    Wu, Jinxian
    Dai, Li
    Zou, Weidong
    Guo, Yongzhen
    Xia, Yuanqing
    2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 4917 - 4922
  • [36] Universal Approximation of a Class of Interval Type-2 Fuzzy Neural Networks Illustrated with the Case of Non-linear Identification
    Castro, Juan R.
    Castillo, Oscar
    Melin, Patricia
    Rodriguez-Diaz, Antonio
    Mendoza, Olivia
    PROCEEDINGS OF THE JOINT 2009 INTERNATIONAL FUZZY SYSTEMS ASSOCIATION WORLD CONGRESS AND 2009 EUROPEAN SOCIETY OF FUZZY LOGIC AND TECHNOLOGY CONFERENCE, 2009, : 1382 - 1387
  • [37] A New Interval Type-2 Fuzzy Aggregation Approach for Combining Multiple Neural Networks in Clustering and Prediction of Time Series
    Ramirez, Martha
    Melin, Patricia
    INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2023, 25 (03) : 1077 - 1104
  • [38] Optimization of Ensemble Neural Networks with Type-2 Fuzzy Response Integration for Predicting the Mackey-Glass Time Series
    Pulido, Martha
    Melin, Patricia
    Castillo, Oscar
    2013 WORLD CONGRESS ON NATURE AND BIOLOGICALLY INSPIRED COMPUTING (NABIC), 2013, : 16 - 21
  • [39] Optimization of interval type-2 fuzzy systems for image edge detection
    Gonzalez, Claudia I.
    Melin, Patricia
    Castro, Juan R.
    Castillo, Oscar
    Mendoza, Olivia
    APPLIED SOFT COMPUTING, 2016, 47 : 631 - 643
  • [40] A Class of Interval Type-2 Fuzzy Neural Networks illustrated with application to Non-linear Identification
    Castro, Juan R.
    Castillo, Oscar
    2013 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2013,