摘要
在数据挖掘领域里,SOM神经网络聚类是典型的基于模型思想的聚类方法。本文阐述了SOM神经网络的工作过程、算法的训练过程及应用。通过对我国各地区GDP数据进行聚类分析,可以及时了解各地区经济实力等重要的信息,对各级政府政策制定及宏观调控都具有非常重要的现实意义。
In the field of data mining, SOM neural network clustering is a typical model-based cluster- ing method.This paper briefly introduces SOM neural network work process,Algorithm training process and application. Through various regions of China＇s GDP data for cluster analysis, Can keep abreast of the various areas of economic strength and other important information ,Governments at all levels of policy-making and macro-control are very important practical significance.
出处
《情报科学》
CSSCI
北大核心
2009年第6期874-876,893,共4页
Information Science
关键词
数据挖掘
聚类分析
神经网络
data mining
clustering analysis
neural network
