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SUMMARY:Engineering-Driven Statistical Adjustment and Calibration - Vengaz
 hiyil\, RJ (Georgia Tech)
DTSTART:20110830T140000Z
DTEND:20110830T143000Z
UID:TALK32564@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:There can be discrepancy between physics-based models and real
 ity\, which can be reduced by statistically adjusting and calibrating the 
 models using real data. Gaussian process models are commonly used for capt
 uring the bias between the physics-based model and the truth. Although thi
 s is a powerful approach\, the resulting adjustment can be quite complex a
 nd physically non-interpretable. A different approach is proposed here whi
 ch is to postulate adjustment models based on the engineering judgment of 
 the observed discrepancy. This often leads to models that are very simple 
 and easy to interpret. The approach will be illustrated using many real ca
 se studies.\n
LOCATION:Seminar Room 1\, Newton Institute
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