The phrase "a dynamic selection" is correct and usable in written English.
It can be used in contexts where you are referring to a choice or option that is flexible and can change based on certain criteria or conditions.
Example: "The software allows for a dynamic selection of features based on user preferences."
Alternatives: "an adaptive choice" or "a flexible option."
To attempt to control inbreeding and maximize response to selection, Wray and Goddard [ 4] proposed a dynamic selection principle, which places a penalty on the co-ancestry of the selected animals.
A dynamic ensemble includes a dynamic selection module for choosing the best ensemble given a test instance.
The sequential design problem entails a dynamic selection of nodes for data collection, where the goal is to maximize utility, here defined via entropy or total expected profit.
AWFM is an extension of weighted fuzzy mean (WFM) filter by linking a fuzzy detector and a dynamic selection procedure to WFM in order to overcome the drawback of WFM in fine signal preservation.
In this paper we study three major milestones to do this encoding: the conceptual computational tree, the use of normal classes and signed permutations, and a dynamic selection of the decomposition.
We propose to include mutiple crossover and mutation operators with a dynamic selection scheme into a multiobjective genetic algorithm in order to choose the best crossover operator to be used at any given time.
Supporting this explanation, the only study of symbolic distance reported herein that also failed to find IPS activation using whole-brain analysis employed a similarly dynamic selection task in which participants were told to judge whether a visually displayed number was smaller or larger than a reference number based on a criterion that changed throughout the experiment.
During verification, a new dynamic selection strategy based on the K-nearest-oracles (KNORA) algorithm and on Output Profiles selects the most accurate EoCs to classify a given input signature.
Finding an optimal dynamic selection strategy is tricky since due to the complementarity principle the value of a particular patch depends on the presence of other patches in the network – including those that have not yet been selected.
Moreover, we try an innovative ensemble classifier building method called LibD3C [ 11], which is a hybrid method using k-means clustering on the distance matrix between classifiers, built from their distances between classification output distributions over the training sample, and a combination of dynamic selection and circulation of the selected classifiers.
In our approach, we employed a new type of ensemble classifier called LibD3C [ 32], which is a library for dynamic selection and circulating combination based on clustering.
