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Exact(2)
The latter solves large-scale optimization problems in considerably less computational time.
It was shown via numerical examples that the Root algorithm demands considerably less computational time than the Opt algorithm and the iterative approximative algorithms.
Similar(58)
We find that our algorithm requires substantially less computational time (especially for large portfolios) but is slightly less accurate.
Since, the stochastic structural response is obtained in the frequency domain from the power spectral density function of the excitation, the proposed approach is very efficient, robust and requires considerably less computational effort than time history analysis.
At lower accuracies, they demand less computational time and computer memory than the alternatives.
The reduced model is of considerably lower order than the original one and requires much less computational time.
This approach is simpler and requires less computational time.
The results of this analysis show that ETA can estimate THA as well as IDA, with considerably less computational effort.
The nonlinear formulation only has one constraint and requires considerably less computational effort than a linear programming formulation.
What is more, our method costs less computational time to get error levels less than 10−2.
A viable alternative that is adequate for many applications is to use statistical downscaling, which has the advantage of requiring considerably less computational resources.
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