摘要
介绍了重介质悬浮液密度在整个选煤过程中的重要性,综合神经网络和模糊控制的优点,提出了一种基于模糊神经网络的悬浮液密度估算方法。以模糊估算器抽象出来的模糊规则表作为神经网络的学习样本,利用神经网络的自学习能力,不断对网络权值和激活函数的参数进行修改,实现了在线修改模糊推理规则的目的。
The significance of the density of the dense-medium suspension during the coal separation course is introduced.Integrating the advantages of neural network and fuzzy control,a method of estimating the suspension density based on fuzzy neural network（FNN） is proposed.The fuzzy rule table abstracted by fuzzy estimator serves as learning sample for neural network,and parameters such as network weight and activation function are continuously revised by using self-taught ability of neural network.Thus online revising of fuzzy inference rules is realized.
出处
《矿山机械》
北大核心
2011年第9期96-99,共4页
Mining & Processing Equipment
关键词
重介选煤
密度
模糊神经网络
估算
dense-medium separation
density
fuzzy neural network
estimation
