Gillblad, Daniel and Steinert, Rebecca and Holst, Anders (2008) Fault-tolerant incremental diagnosis with limited historical data. In: International Conference on Prognostics and Health Management 2008 (PHM'08), 6-9 October 2008, Denver, Colorado, USA.
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We describe a novel incremental diagnostic system based on a statistical model that is trained from empirical data. The system guides the user by calculating what additional information would be most helpful for the diagnosis. We show that our diagnostic system can produce satisfactory classification rates, using only small amounts of available background information, such that the need of collecting vast quantities of initial training data is reduced. Further, we show that incorporation of inconsistency-checking mechanisms in our diagnostic system reduces the number of incorrect diagnoses caused by erroneous input.
|Item Type:||Conference or Workshop Item (Paper)|
|Deposited By:||L-H Orc Lönn|
|Deposited On:||06 Apr 2009|
|Last Modified:||18 Nov 2009 16:24|
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