自组织神经网络用于地质样品分类  

THE APPLICATION OF SELF-ORGANIZING NEURAL NET TO THE CLASSIFICATION OF GEOLOGICAL SAMPLES

作　　者：王硕儒[1] 赵举孝 范德江[1] 

机构地区：[1]青岛海洋大学,青岛266003 [2]地矿产部航遥感中心,北京100083

出　　处：《物探与化探》1997年第2期139-144,共6页Geophysical and Geochemical Exploration

摘　　要：地质样品的分类是地质学中一个重要问题。本文提出用一种神经网络———ART2模型来实现自动分类。该方法简单、实用 ,分类效果令人满意。The classification of geological samples is one of the important problems in geology. The present paper presents a sort of neural net--ART2 model for realizing automatic classification. Being simple and practical, the method shows satisfactory classification result. The application of the neural net proves that it has dual functions of producing both optimum number of classification and optimum classification.

关 键 词：地质样品 聚类分析 自组织 神经网络 分类 

分 类 号：P624.4[天文地球—地质矿产勘探]