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

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

The benchmark functions. by Shuhui Yu (1535500)

Automatic cropping algorithm. by Thomas W Georgi (12427189)

Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

Comparison of optimization performance of six ABC algorithms. by Shuhui Yu (1535500)

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... by 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. …”

Sets of best performing parameters obtained after gridsearching through different values for each classification algorithm. by Adhiraj Nath (17118269)

ROC and precision plots of SVM showing the details of accuracy. by Abeer Aljohani (18497914)

Subjects:

Flowchart showing the basic functioning of our implementation of the algorithm described in this paper. by Pablo Rodríguez-Sánchez (6711683)

“…<p>Flowchart showing the basic functioning of our implementation of the algorithm described in this paper.…”

Fitting of cumulative number of cases in a pre-lockdown period. by Wang Xiang (5435141)

Subjects:

SP results of algorithms in the CEC 2009 test functions. by Vahid Goodarzimehr (21343124)

MS results of algorithms in the CEC 2009 test functions. by Vahid Goodarzimehr (21343124)

Algorithm. by Daniel Sanchez-Taltavull (11654630)

Pre-trained protein language model. by Youzhi Zhang (728859)

“…In order to obtain large data samples, this work integrates and extracts data from the datasets of ASEdb, BID, SKEMPI and dbMPIKT to generate a new dataset, and adopts the SMOTE algorithm to expand positive samples to form the training set. …”

Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

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

Subjects:

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

Algorithm used for important sampling of the likelihood function. by Zhiyong Huang (3620000)

Convergence curves of different algorithms on the benchmark functions. by Aihua Guo (13267712)