The Rule Criteria and Pruning Strategy Based on D-FNN Algorithm Research

ZUO Jun; ZHOU Ling; LI Xiaodong

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The Rule Criteria and Pruning Strategy Based on D-FNN Algorithm Research

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- The Rule Criteria and Pruning Strategy Based on D-FNN Algorithm Research
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 54, Issue 5, Pages: 43-48(2015)
- 作者机构：
  
  佛山科学技术学院电子与信息工程学院,广东,佛山,528000
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2015，
  
  Published Online：25 September 2015，
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ZUO Jun, ZHOU Ling, LI Xiaodong. The Rule Criteria and Pruning Strategy Based on D-FNN Algorithm Research. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 54(5):43-48(2015)
DOI：

ZUO Jun, ZHOU Ling, LI Xiaodong. The Rule Criteria and Pruning Strategy Based on D-FNN Algorithm Research. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 54(5):43-48(2015) DOI：

摘要

提出了一种D-FNN结构及其学习算法，该D-FNN的结构基于径向基神经网络。模糊规则的产生由输出误差或可容纳边界的有效半径决定。修剪技术的应用，使得网络结构能够保持紧凑，学习速度快，确保系统的泛化能力。对所提算法作了详细探讨，并与相关算法作比较，从而发现了D-FNN的独特思想。编写了D-FNN的仿真程序，对具体案例进行了仿真。结果表明，D-FNN具有紧凑的结构和优秀的性能。

Abstract

A new structure for D-FNN and its learning algorithm are put forward. The structure of this D-FNN is based on RBF neural network. In the new algorithm and structure

generation of fuzzy rule is determined by the output error and the effective radius of the accommodate boundary. At the same time

the application of pruning technology makes a simple network structure

fast learning speed and generalization ability for system. The new algorithm is discussed in detail and compared with correlated algorithms. By these technology methods

the unique advantage of D-FNN is found. At last

simulation program for D-FNN are wrote and the concrete cases are run in the program. Simulation results show that the new D-FNN has a compact structure and excellent performance.

关键词

动态模糊神经网络径向基函数模糊规则修剪策略

Keywords

dynamic fuzzy neural network (D-FNN)radial basis function (RBF)fuzzy rulepruning strategy

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Research on D-FNN Algorithm with the Combination of Column Pivot#br# SVD-QR Method Pruning Strategy and Parameters Adjustment

Dynamic Fuzzy Neural Network Method Research of the Glide Window and Pruning Technology

Research on Adaptive Dynamic Fuzzy Neural Network #br# Algorithms with Gauss Activation Function and Eigenvalue #br# Decomposition Pruning Technologies

Research Based on D-FNN Algorithm on the Nonlinear Dynamic System Identification

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Related Institution

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School of Science, Foshan University

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