DocumentCode :
2097566
Title :
Comparative Investigation of BP and RBF Neural Network on Identifying Reliability of Communication Networks
Author :
Song, Bin ; Peng, Zhenghong
Author_Institution :
Sch. of Electr. Eng., Wuhan Univ., Wuhan, China
Volume :
2
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
376
Lastpage :
379
Abstract :
In this paper, BP and RBF models for evaluating the running reliability of communication networks is presented on the basis of artificial neural network. The applicability of the two neural networks are investigated to the reliability of communication networks system. The study shows that the model established by BP network has a good general ability and a slow impending speed, on the other hand, the model established by RBF neural network has a bad general ability and a fast impending speed. The two models can provide well base to reliability of communication networks for analysis and calculation and the optimum of structure. The simulation results highly indicate the usefulness of the method pointed out in this study. The conclusion will provide theoretical guide for practice application.
Keywords :
backpropagation; radial basis function networks; telecommunication computing; telecommunication network reliability; backpropagation neural network; communication network reliability; radial basis function neural network; Analytical models; Artificial neural networks; Business communication; Communication networks; Computer network reliability; Computer networks; Electronic mail; Neural networks; Reliability theory; Telecommunication network reliability; BP neural network; RBF neural network; communication network; reliability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
Type :
conf
DOI :
10.1109/ISCSCT.2008.114
Filename :
4731644
Link To Document :
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