黑龙江科技学院学报Issue(2)：116-118,139,4.
基于人工神经网络的水力旋流器分离性能预测
Prediction of artificial neural network-based hydrocyclones classification performance
摘要
Abstract
Aimed at addressing complex separating process of hydrocyclone which suffers from a typical multidimensional nonlinear relationship between the influencing factors and the performance indexes,compounded by the previous theoretical and empirical models available often under simplifying some conditions and limited in prediction capability,this paper features a three-layers BP neural network model capable of predicting separated particle size,production capacity,the underflow concentration and so on,with the structure and operating parameters,for comprehensive prediction of the separator performance index.Comparison between the results derived from the BP network and the previous model associated with the production capacity shows that BP neural network boasts the prediction precision of 16.64%,comparing favourably with 20.88% for Pang Xueshi law,the best of all traditional prediction formula.The BP neural theoretical model proves a reliable way for predicting classification performance of hydrocyclones.关键词
水力旋流器/BP神经网络/磁铁矿粉/分级性能Key words
hydrocyclone/BP neural network/magnetite/classification performance分类
矿业与冶金引用本文复制引用
韦鲁滨,杜长江,王月丽,徐欢..基于人工神经网络的水力旋流器分离性能预测[J].黑龙江科技学院学报,2012,(2):116-118,139,4.基金项目
国家自然科学基金项目 （）
国家重点基础研究发展计划（973计划）项目 （）
中央高校基本科研业务费专项资金项目 （）
高等学校博士学科点专项科研基金项目 （）
