DocumentCode :
2702931
Title :
A Method about Load Distribution of Fishing Mills Based on RBF Neural Network
Author :
Wang, Yan ; Liu, Dongdong ; Yang, Quan ; Sun, Yikang
Author_Institution :
Univ. of Jinan, Jinan
fYear :
2007
fDate :
15-19 Dec. 2007
Firstpage :
51
Lastpage :
54
Abstract :
This paper use RBF neural networks to establish finishing thickness and rolling force models. Compared with those finishing models which have or have not traditional models as input, the importance of traditional models in application of neural networks is obvious. In order to improve the predictive precision of finishing thickness and rolling force, using BP and RBF neural networks to establish finishing models, the result indicates that the model of load distribution based on RBF neural network is more accurate, also solving over-fitness problems in network application.
Keywords :
aquaculture; backpropagation; fishing industry; radial basis function networks; BP neural network; RBF neural network; finishing thickness; fishing mills; load distribution; rolling force model; Clustering algorithms; Finishing; Function approximation; Genetic algorithms; Milling machines; Neural networks; Optimization methods; Predictive models; Production; Temperature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security Workshops, 2007. CISW 2007. International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-0-7695-3073-4
Type :
conf
DOI :
10.1109/CISW.2007.4425444
Filename :
4425444
Link To Document :
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