DocumentCode
2329358
Title
Unascertained RBF Neural Network and its Application in Fault Diagnosis
Author
Pang, Yanjun ; Pan, Wei
Author_Institution
Coll. of Sci., Hebei Univ. of Eng., Handan
fYear
2009
fDate
23-24 May 2009
Firstpage
1
Lastpage
5
Abstract
In this paper, unascertained RBF neural network is founded. The features are as follows: integrate the advantages of unascertained system and neural network; use prior knowledge of the known samples; present a new algorithm to compute membership, and the network output is reasonable and has good interpretability besides. This method applying unascertained RBF neural network to fault diagnosis obtains very good effect.
Keywords
fault diagnosis; radial basis function networks; fault diagnosis; network output; unascertained RBF neural network; unascertained system; Artificial neural networks; Cognition; Computer networks; Educational institutions; Electronic mail; Fault diagnosis; Neural networks; Observers; Parameter estimation; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Business and Information System Security, 2009. EBISS '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-2909-7
Electronic_ISBN
978-1-4244-2910-3
Type
conf
DOI
10.1109/EBISS.2009.5138141
Filename
5138141
Link To Document