Paper Title:
Application of RBF Neural Network in Dynamic Weighing
  Abstract

In order to improve the dynamical respond of the weighing system and to meet the demand of rapid weighing, a new method based on radial basis function neural network (RBFNN) is introduced in this paper. The dynamic system is described as a network and the output values of steady state are predicted by an on-line modeling before the platform has settled to the steady state. The sample weight is calculated according to weighted moving average. The experimental results proved that the neural network method in this paper can be used to effectively reduce the weighing time and to increase the accuracy simultaneously.

  Info
Periodical
Advanced Materials Research (Volumes 383-390)
Chapter
Chapter 5: Computer-Aided Design in Materials Engineering
Edited by
Wu Fan
Pages
1495-1499
DOI
10.4028/www.scientific.net/AMR.383-390.1495
Citation
Q. Jiang, X. Q. Shen, J. H. Cai, Y. Yao, "Application of RBF Neural Network in Dynamic Weighing", Advanced Materials Research, Vols. 383-390, pp. 1495-1499, 2012
Online since
November 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Chun Mei Zhu, Chang Peng Yan, Xiao Li Xu, Guo Xin Wu
Abstract:In order to improve the efficiency and accuracy of the prediction of expressway traffic flow, this paper, based on the characteristics of the...
4400
Authors: Hui Zhen Yang, Wen Guang Zhao, Wei Chen, Xu Quan Chen
Chapter 8: System Modeling and Simulation
Abstract:Wavelet Neural Network (WNN) is a new form of neural network combined with the wavelet theory and artificial neural network. The wavelet...
4847