Sentence examples for expected running time from inspiring English sources

To find the value of that maximizes the expected utility (to within a convex-hull approximation) while ensuring that the expected running time of the system is at least some fixed value, we simply do a search over to find the value that minimizes.

Theoretical arguments and extensive simulations determined the resulting expected running time.

In the special case of integer sorting, we present an algorithm with linear expected running time that can tolerate O(√n) faults.

Because of this, for these two problems, we find that a multi-objective EA with recombination enabled achieves a better expected running time than any known EAs with recombination disabled.

The expected running time of PADE could be reduced by using more powerful mutation formula or by identifying search patterns in archive solutions, which we would investigate further in the future.

For clarity and brevity, the terms expressed in the flowchart are defined as : M s (market share); P t (total output); t b (mean time to maintain machines i); t e (expected running time of machine (1); Q c (capacity of plant); P actual (actual production); P i (total loss due to maintenance activity); and µ i (range of severity).

Unlike specifications of traditional systems, where the behaviors are static descriptions of the expected run-time operation, our approach allows the application to define dynamic behaviors.

Given O(n3) processors and a known upper bound Λ=Λ l,m) for the length of longest paths, the expected run-times of parallelized versions are O(n log n log Λ) for the first cooling schedule and O(n2 (log3/2n m1/2 log Λ) for the second cooling schedule, where n=lm is the number of tasks.

The film's expected run-time was fifteen minutes and was billed by the Thanhouser Company as having many novelties and being of a comedic nature.

As the expected run-time increases, the likelihood of successfully completing the calculation before the next failure tends to zero.

As expected, the running time scales linearly with the number of bootstrap samples per condition, and thus generating M = 20 bootstrap samples per condition is nearly 10 times faster than generating M = 200 of them.