DocumentCode
1564371
Title
Monitoring Approach Using Recurrent Radial Basis Function Neural Networks and Neuro-Fuzzy Systems
Author
Racoceanu, Daniel ; Zerhouni, Noureddine
Author_Institution
Dept. of Sci., Franche-Comte Univ., Besancon
Volume
2
fYear
2005
Firstpage
678
Lastpage
682
Abstract
Multiple reconfiguration and complexity of modern production systems lead to design intelligent monitoring aid systems. The use of artificial intelligence techniques in order to exploit their learning and human experience modeling seems very promising. In this paper, we propose a new monitoring aid system composed by a dynamic neural network detection tool and a neuro-fuzzy diagnosis tool. Learning capabilities due to the neural structure permit us to update the monitoring aid system. The neuro-fuzzy network provides an abductive diagnosis. Moreover it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause
Keywords
computerised monitoring; production engineering computing; radial basis function networks; recurrent neural nets; abductive diagnosis; artificial intelligence techniques; dynamic neural network detection tool; intelligent monitoring aid systems; modern production systems; neuro-fuzzy diagnosis tool; recurrent radial basis function neural networks; Artificial intelligence; Artificial neural networks; Fuzzy neural networks; Humans; Intelligent systems; Learning; Monitoring; Production systems; Radial basis function networks; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9422-4
Type
conf
DOI
10.1109/ICNNB.2005.1614721
Filename
1614721
Link To Document