DocumentCode
3731231
Title
The mill load modeling of combined grinding system based on RBF neural networks
Author
Chuanjiang Yu; Jianjun Zheng; Tao Shen
Author_Institution
School of Electrical Engineering, University of Jinan, China
fYear
2015
Firstpage
2085
Lastpage
2090
Abstract
In order to get the mill load modeling of combined grinding system in normal working condition, this paper proposes a method based on the RBF neural network. The neural network uses three kinds of kernel functions that are Gauss kernel function, multiquadric kernel function and inverse multinuclear kernel function. Using the gradient descent method trains the neural network. With the comparison of three neural network´s fitting error, I´ve come to the conclusion that the RBF neural network based on Gauss function is more accurate.
Keywords
"Artificial neural networks","Training"
Publisher
ieee
Conference_Titel
Chinese Automation Congress (CAC), 2015
Type
conf
DOI
10.1109/CAC.2015.7382848
Filename
7382848
Link To Document