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.
出处
《矿业研究与开发》
CAS
北大核心
2006年第5期51-54,共4页
Mining Research and Development
