As for Fig 2, we present failure rates as a function of the cohort size (vertical axis) versus the number of distractors (horizontal axis), for the Smyth and McClave baseline algor... حسب Daniela Huppenkothen (9174507)

"…We note that the middle row is a special case: here, <i>f</i>_target only corresponds to the proportions of the embedded cohort, while “success” for these two panels is defined as recovering maximally diverse cohorts, as this particular algorithm is designed to do. The bottom row shows the same simulations as the middle row, but presents successes and failures when the targets that generated the embedded cohort are applied instead of the balanced targets that are part of the baseline’s objective function. …"

Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective حسب Xiangyang Jia (10026932)

Left: the algorithm’s best estimate of where to put breakpoints for each number of breakpoints considered. حسب Zhengtian Li (5076704)

Results obtained by different algorithms on 23 benchmark functions. حسب Yuqi Xiong (12343771)

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Table_2_Visuospatial, oculomotor, and executive reading skills evolve in elementary school, and errors are significant: a topological RAN study.pdf حسب Mario Lecce (18777553)

Table_1_Visuospatial, oculomotor, and executive reading skills evolve in elementary school, and errors are significant: a topological RAN study.pdf حسب Mario Lecce (18777553)

Convergence curves obtained by different algorithms on 23 benchmark functions. حسب Yuqi Xiong (12343771)

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Different algorithms in 23 benchmark functions to obtain partial boxplot. حسب Yuqi Xiong (12343771)

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Results obtained by different algorithms on CEC2022 benchmark functions. حسب Yuqi Xiong (12343771)

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Algorithm. حسب Daniel Sanchez-Taltavull (11654630)

Average function evaluation times of the three optimization algorithms. حسب Shuhui Yu (1535500)

Convergence curves obtained by different algorithms on CEC2022 benchmark functions. حسب Yuqi Xiong (12343771)

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Prediction performance of different optimization algorithms. حسب Ali-Kemal Aydin (10968731)

Investigate the variation of the cost function in situations where many obstacles and other robots are detected. حسب Quoc Bao Diep (18452207)

Comparison of deconvolution and optimization algorithms on a batch of data. حسب Ali-Kemal Aydin (10968731)

Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. حسب Yuanchen Zhao (12905580)

Framework of the proposed signal control algorithm. حسب Hyosun Lee (1567246)

Compare algorithm parameter settings. حسب Yuqi Xiong (12343771)

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The benchmark functions. حسب Shuhui Yu (1535500)

A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. حسب Boluwatife Ikwunne (22238697)