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
收藏
页码：3259 / 3264
页数：6
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