A hierarchical fuzzy-clustering approach to fuzzy modeling

被引：87

作者：

Tsekouras, G ^{[1
]}

Sarimveis, H ^{[1
]}

Kavakli, E ^{[1
]}

Bafas, G ^{[1
]}

机构：

[1] Natl Tech Univ Athens, Sch Chem Engn, Athens 11580, Greece

来源：

FUZZY SETS AND SYSTEMS | 2005年 / 150卷 / 02期

关键词：

ordinary ftizzy partitions; nearest neighbor clustering; optimal fuzzy clustering; fuzzy basis functions;

D O I：

10.1016/j.fss.2004.04.013

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper introduces a new method for fuzzy modeling based on a hierarchical fuzzy-clustering scheme. The method consists of a sequence of steps aiming towards developing a Takagi-Sugeno (TS) fuzzy model of optimal structure, where the fuzzy sets in the premise part are of Gaussian type. Starting from an initial ordinary fuzzy partition of the input space, the algorithm performs a nearest-neighbor search and groups the original input training data into a number of clusters. The centers of these clusters are further processed using an optimal fuzzy clustering technique, which is based on the weighted fuzzy c-means algorithm. The resulted optimal fuzzy partition defines the number of fuzzy rules and provides an initial estimation for the system parameters, which in a next step are fine tuned using the well-known gradient-descend algorithm. The proposed method is successfully applied to three test examples where the produced fuzzy models prove to be very accurate, as well as compact in size. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：245 / 266

页数：22

共 23 条

[21] A fuzzy system based active set algorithm for the numerical solution of the optimal control problem governed by partial differential equation [J].

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EUROPEAN JOURNAL OF CONTROL, 2020, 54 :99-110

[22] An accurate and efficient skew estimation technique for South Indian documents: A new boundary growing and nearest neighbor clustering based approach [J].

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[23] An accurate and efficient skew estimation technique for south Indian documents: A new boundary growing and nearest neighbor clustering based approach [J].

Aradhya, V.N.M. ;

Kumar, G.H. ;

Shivakumara, P. .

International Journal of Robotics and Automation, 2007, 22 (04) :272-280

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