Experimental Design for Inverse Modelling: From Real to Virtual and Back
32 mins 37 secs,
474.78 MB,
MPEG-4 Video
640x360,
29.97 fps,
44100 Hz,
1.94 Mbits/sec
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About this item
| Description: |
Challenor, P
Wednesday 11th April 2018 - 10:00 to 10:30 |
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| Created: | 2018-04-11 14:52 |
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| Collection: | Uncertainty quantification for complex systems: theory and methodologies |
| Publisher: | University of Cambridge |
| Copyright: | ah984 |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | Inverse modelling requires both observations in the real world as well as runs of the computer model. As our inverse modelling method we look at history matching which uses waves of computer model runs to find areas of input space where the model is implausible and thus can be ruled out. However if we reduce the uncertainty on our observations we also rule out additional space. Given the relative costs of model runs and real world observations can we find a method of deciding which is best to do next? Using an example in c radiology we examine the interplay between taking real world observations and running additional computer experiments and explore some possible strategies. . |
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