| Download | - View accepted manuscript: Automating Model Acquisition by Fault Knowledge Re-use: Introducing the Diagnostic Remodeler Algorithm (PDF, 526 KiB)
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| Author | Search for: Abu-Hakima, Suhayya |
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| Format | Text, Article |
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| Conference | Proceedings of the Canadian Artificial Intelligence Conference, May 21-24,1996., Toronto, Ontario, Canada |
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| Abstract | The paper addresses the problem of automated model acquisition through the re-use of fault knowledge. The Diagnostic Remodeler (DR) algorithm has been implemented for the automated generation of behavioural component models with an explicit representation of function by re-using fault-based knowledge. DR re-uses as its first application the fault knowledge of the Jet Engine Troubleshooting Assistant (JETA). DR extracts a model of the Main Fuel System using real-world engine fault knowledge and two types of background knowledge as input: device dependent and device independent background knowledge. To demonstrate DR's generality, it has also been applied to a coffee maker fault knowledge base to extract the component models of a full coffee device. |
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| Publication date | 1996 |
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| Language | English |
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| NRC number | NRCC 39203 |
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| NPARC number | 5765207 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | ac8bfbd9-2b51-43c2-8d96-36c83055f97d |
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| Record created | 2009-03-29 |
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| Record modified | 2020-03-20 |
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