A conditional clustering algorithm using self-organizing map

被引：0

作者：

Tateyama, T ^{[1
]}

Kawata, S ^{[1
]}

Ohta, H ^{[1
]}

机构：

[1] Tokyo Metropolitan Univ, Grad Sch Engn, Hachioji, Tokyo 158, Japan

来源：

SICE 2003 ANNUAL CONFERENCE, VOLS 1-3 | 2003年

关键词：

SOM; conditional clustering; machine-part matrix; plant layout planning;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new clustering method using SOM is proposed. In our method, we can specie, three parameters, the number of clusters, maximum and minimum number of elements in a cluster. The proposed mehtod consists of three parts: SOM's learning, setting of classification lines, and ajusting clusters. We applied this method to a plant layout planning problem and satisfactory results were obtained.

引用

页码：3259 / 3264

页数：6

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