Details
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Type:
Story
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Status: Done
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Resolution: Done
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Fix Version/s: None
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Component/s: pipe_tasks
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Labels:
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Story Points:3
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Epic Link:
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Sprint:AP F18-6
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Team:Alert Production
Description
With larger numbers of DCR subfilters (e.g. 5) the dcrModel solution can sometimes oscillate between iterations of forward modeling. This results in premature termination of the modeling loop, because the convergence may improve by a large amount in one iteration, and by a very small amount in the next, triggering the convergence end condition. One solution is to set a small enough gain on the new model solutions so that modeling converges smoothly, but then more iterations are required to reach the same level of convergence. Instead, the gain should adapt to how well the model is improving compared to predictions.
Would you be willing to review these changes? The new gain calculation is essentially a Kalman filter, though I don't want to pull in a new package and dependency since it's straightforward to implement.
Also, note that since the pull request is in
{pipe_tasks}, it might not show up as a link in Jira.