数据挖掘及其在矿业中的应用研究  

Study on Data Mining and Its Application in Mining Industry

作　　者：李学锋[1] 钟叔玉[2] 

机构地区：[1]广西大学资源与环境学院,广西南宁530004 [2]昆明理工大学经济与管理学院,云南昆明650093

出　　处：《矿业研究与开发》2006年第5期51-54,共4页Mining Research and Development

摘　　要：介绍了数据挖掘的概念及矿业中常用的数据挖掘模型,如神经网络模型、时间序列与周期分析模型、灰色模型等等。以对在某矿业公司选厂为研究对象,应用人工神经网络模型进行选矿效果指标预测,结果表明,预测值与实际的选矿效果指标值吻合良好。This paper introduces the concept of data mining and their model usually used in mining industry, such as artificial neural network, schedule sequential and cycle analysis model, grey model, etc. Taking a certain ore - concentration plant as studied object, a BP model is applied to predict the concentration indexes, and the results indicate that the predicted concentration indexes are in well accordance with the practical production indexes.

关 键 词：数据挖掘 神经网络模型 选矿指标 

分 类 号：TD178[矿业工程—矿山地质测量] TP39[自动化与计算机技术—计算机应用技术]