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
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;
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
DOI :
10.1109/EBISS.2009.5138141
