A tabu search-based algorithm for the Fuzzy Clustering Problem

被引：48

作者：

Al-Sultan, KS ^{[1
]}

Fedjki, CA ^{[1
]}

机构：

[1] King Fahd Univ Petr & Minerals, Dept Syst Engn, Dhahran 31261, Saudi Arabia

来源：

PATTERN RECOGNITION | 1997年 / 30卷 / 12期

关键词：

fuzzy clustering; fuzzy C-means algorithm; tabu search technique; global optimization;

D O I：

10.1016/S0031-3203(97)00020-4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Fuzzy Clustering Problem (FCP) is a mathematical program which is difficult to solve since it is nonconvex, which implies possession of many local minima. The fuzzy C-means heuristic is the widely known approach to this problem, but it is guaranteed only to yield local minima. In this paper, we propose a new approach to this problem which is based on tabu search technique, and aims at finding a global solution of FCP. We compare the performance of the algorithm with the fuzzy C-means algorithm. (C) 1997 Pattern Recognition Society. Published by Elsevier Science Ltd.

引用

页码：2023 / 2030

页数：8

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