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Although for local resource allocation only a one step ahead prediction is needed, our VM agent predicts several steps ahead into the future to support overload detection through long-term prediction.
Accurate laminar-turbulent transition prediction is needed for many practical problems.
Predicting flows of oil and water through oil reservoirs is an example of a complex system where accuracy in prediction is needed primarily for financial reasons.
This kind of prediction is needed in order to account for potential changes in a long-term future operational environment of marine and coastal structures.
Possible use cases include emergency service assistance, teaching environments, augmented reality or indeed any such case where large computational resources are unavailable and a system prediction is needed.
In our study, approximately 41% of patients responded to fluids, which explains why a fluid responsiveness prediction is needed before volume expansion.
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In order to apply Q-learning, which is one way of reinforcement learning, two kinds of prediction are needed for each hunter agent.
Further studies to assess the performance of the models proposed here and also to compare them with conventional models used in genome-wide prediction are needed.
The accurate models for air pollutant prediction are needed because such models would allow forecasting and diagnosing potential compliance or non-compliance in both short- and long-term aspects.
A more precise prognosis of the risk of relapse and a response prediction are needed.
Future studies directly comparing indexing methods in clinical event prediction are needed to establish the best method for indexing LA size.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com