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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Ariton, Viorel
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (4/4 displayed)
- 2010The Diagnosis by Abduction using Human Expert Knowledge
- 2010Combined deep and shallow knowledge in a unified model for diagnosis by abduction
- 2007COMBINED DEEP AND SHALLOW KNOWLEDGE IN A UNIFIED MODEL FOR DIAGNOSIS BY ABDUCTION
- 2006Combined Deep And Shallow Knowledge In A Unified Model For Diagnosis By Abduction
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article
Combined Deep And Shallow Knowledge In A Unified Model For Diagnosis By Abduction
Abstract
ault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causes-effects) but also deep knowledge(as structural / functional modularization and models on behavior). The paper proposes a unified approach on diagnosis by abduction based onplausibility and relevance criteria multiple applied, in a connectionist implementation. Then, it focuses elicitation of deep knowledge on targetconductive flow systems – most encountered in industry and not only, in the aim of fault diagnosis. Finally, the paper gives hints on design andbuilding of diagnosis system by abduction, embedding deep and shallow knowledge (according to case) and performing hierarchical fault isolation,along with a case study on a hydraulic installation in a rolling mill plant.