Sentence examples for using a simple greedy from inspiring English sources

Exact(6)

A low energy conformer is found using a simple greedy algorithm.

The ten masks for the indexes are chosen using a simple greedy algorithm to maximize sensitivity gain from each additional mask (see Supplemental Materials S1 for more details).

For runtime reasons the assignment of patients to vehicle locations will be determined using a simple greedy procedure.

It uses BLAST scores to assign statistical significance, matches pairs that reach that level of significance, then constructs clusters using a simple, greedy, single-linkage clustering method.

The assignment of patients to locations will be determined using a simple greedy procedure.> To start with all vehicles will be located randomly across all potential locations, while making sure capacity restrictions at those locations are obeyed.

Using a simple greedy algorithm (see Methods section) we find that our ability to achieve high (>95%) coverage for randomly generated multi-node graphs critically depends on the compatibility probability, P, (or conversely the interaction probability (1-P)) as well as the target level of multiplexing.

Similar(53)

Typical unicast schemes use a simple greedy approach, which finds the route from the BS to each SS that consumes the least amount of the resource.

For the clustered distribution of BTs, we used a simple greedy scheme to add BTs one by one to the network at positions that could cover the highest number of uncovered wireless nodes.

For efficiency considerations, we choose to use a simple greedy algorithm for this step.

BAIT then uses a simple greedy algorithm to reorient the misoriented linkage groups, iteratively inverting the most dissimilar, and recomputing the distance matrix until a reorientation causes no increase in the summed concordance of all groups.

Meanwhile, the baseline algorithm uses a simple random greedy strategy, which first finds the best team, then randomly removes a worker from the best team from the set of workers, and iteratively finds the other (k-1) best teams following the two steps above.

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