摘要
采用ＢＰ神经网络原理，对包钢选矿厂浮选过程数据进行处理，建立了基于人工神经网络的浮选精矿品位预测模型。此预测模型的计算值与实测值相比，偏差小于２％，该模型较真实地反映了浮选过程的特征。
he principle of BP neural networks was used to process the data from the floatation course of dressing works in Baotou steel & Iron Co.so as to establish a prediction model of floatation concentrate grade on the basis of neural networks.The calculation value of the prediction meodel was compared with actual measurements resulting in a deviation less than 2%.This model can reflect the feature in the course of floatation fair truly
出处
《矿业研究与开发》
CAS
1998年第1期21-23,共3页
Mining Research and Development
