摘要
以格林函数为激活函数的RBF网络是通用逼近器,它可以逼近任意多元连续函数,具有处理非线性关系的强大潜能,可以快速、准确地预测煤发热量。
The RBF Network with the Green function as the active function is a universal approximator in that it can approximate arbitrarily well any multivariate continuous function. It has the potential of dealing with the nonlinear relationship and can forecast the calorific value of coal quickly and exactly.
出处
《黑龙江大学自然科学学报》
CAS
2003年第1期71-74,77,共5页
Journal of Natural Science of Heilongjiang University
基金
黑龙江省95科技攻关基金资助项目(G97A11-2-07)
关键词
煤发热量
人工神经网络
径向基函数
径向基函数网络
calorific value
artificial neural networks
radial-basis function
RBF
radial-basis func- tion network
