Self-Organizing Neuro-Fuzzy Inference System

被引：0

作者：

Allende-Cid, Hector ^{[1
]}

Veloz, Alejandro ^{[1
]}

Salas, Rodrigo ^{[2
]}

Chabert, Steren ^{[2
]}

Allende, Hector ^{[1
]}

机构：

[1] Univ Tecn Federico Santa Maria, Dept Informat, Valparaiso, Chile

[2] Univ Valparaiso, Dept Ingenier Biomed, Valparaiso, Chile

来源：

PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS | 2008年 / 5197卷

关键词：

ANFIS; Flexible Architecture; Nonlinear modeling;

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：

The architectural design of neuro-fuzzy models is one of the major concern in many important applications. In this work we propose an extension to Rogers's ANFIS model by providing it with a self-organizing mechanism. The main purpose of this mechanism is to adapt the architecture during the training process by identifying the optimal number of premises and consequents needed to satisfy a user's performance criterion. Using both synthetic and real data, our proposal yields remarkable results compared to the classical ANFIS.

引用

页码：429 / +

页数：2

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