Monitoring approach using recurrent radial basis function neural networks and neuro-fuzzy systems

Daniel Racoceanu; Noureddine Zerhouni

Monitoring approach using recurrent radial basis function neural networks and neuro-fuzzy systems

Daniel Racoceanu, Noureddine Zerhouni

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05
Pages	678-682
Number of pages	5
State	Published - 2005
Externally published	Yes
Event	2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05 - Beijing, China Duration: 13 Oct 2005 → 15 Oct 2005

Publication series

Name	Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05
Volume	2

Conference

Conference	2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05
Country/Territory	China
City	Beijing
Period	13/10/05 → 15/10/05

Cite this

Racoceanu, D., & Zerhouni, N. (2005). Monitoring approach using recurrent radial basis function neural networks and neuro-fuzzy systems. In Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05 (pp. 678-682). Article 1614721 (Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05; Vol. 2).

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title = "Monitoring approach using recurrent radial basis function neural networks and neuro-fuzzy systems",

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.",

author = "Daniel Racoceanu and Noureddine Zerhouni",

year = "2005",

language = "English",

isbn = "0780394224",

series = "Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05",

pages = "678--682",

booktitle = "Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05",

note = "2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05 ; Conference date: 13-10-2005 Through 15-10-2005",

}

Racoceanu, D & Zerhouni, N 2005, Monitoring approach using recurrent radial basis function neural networks and neuro-fuzzy systems. in Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05., 1614721, Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05, vol. 2, pp. 678-682, 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05, Beijing, China, 13/10/05.

Monitoring approach using recurrent radial basis function neural networks and neuro-fuzzy systems. / Racoceanu, Daniel; Zerhouni, Noureddine.
Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05. 2005. p. 678-682 1614721 (Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zerhouni, Noureddine

PY - 2005

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N2 - 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.

AB - 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.

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M3 - Conference contribution

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SN - 9780780394223

T3 - Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05

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BT - Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05

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ER -

Monitoring approach using recurrent radial basis function neural networks and neuro-fuzzy systems

Abstract

Publication series

Conference

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