基于人工神经网络系统的选矿指导子模块构建与实现研究  

A Research on Ore-dressing Instruction Sub-module's Construction and Realization Based on Artificial Neural Network Systems

作　　者：刘妍妮[1] LIU Yanni(Shanxi Transportation Vocational and Technical College,Xi＇an,Shanxi 710018,China)

机构地区：[1]陕西交通职业技术学院,陕西西安710018

出　　处：《中国锰业》2018年第3期103-105,共3页China Manganese Industry

摘　　要：从人工神经网络算法的分析出发,对基于人工神经网络系统的选矿指导子模块整体架构与功能进行设计与研究。经验证:若基于BP网络的选矿模型输入不佳,可根据模型输入输出关系对选矿药剂用量进行调整,进而提供可靠的选矿指导依据。Beginning with the analysis on artificial neural network algorithm,the paper makes a design and research on the overall structure and function of ore dressing instruction sub-module＇s based on artificial neural network systems.The experience certificates that,if the import value of mineral processing model is bad,it can make an adjust of mineral dressing agent dosage on the basis of input and output relationship.It provides a reliable selection guide basis.

关 键 词：人工神经网络 BP网络算法 选矿指导 

分 类 号：TD91[矿业工程—选矿]