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A specific case is illustrated by applying the proposed optimization procedure to analyze the optimal rules for a given inlet distributing manifold geometry.
The purpose of this article is to derive optimal rules for SMTs.
The guidance system give advices to travelers based on system optimal rules with user constrains.
Most of the work done in the area of deriving optimal rules was based on an assumption that the observations at each sensor node are conditionally independent.
The majority of optimal rules derived for different decentralized detection application scenarios are based on an assumption that the sensors' observations are statistically independent.
Our new method provides approximately optimal rules for between and within partitions that determine the number of samples allocated to each design location.
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A simulation model is developed and linked with BOBYQA, an efficient optimization algorithm, to determine the optimal rule parameters in a stage-wise manner.
Since the PU has to stop at stage M, we first calculate the optimal stopping rule at stage M−1, then conclude the optimal rule at stage M−2, and so on until we get the optimal rule at stage 1.
We provide an adaptive, Markov model-based solution for learning the optimal rule when stream dynamics are initially unknown.
To find the optimal rule base of ANFIS, a new "top down" rules reduction method is suggested.
We show that the decision rules in mTPI correspond to an optimal rule under a formal Bayesian decision theoretic framework.
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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