Pseudo-code of MWOA algorithm. by Yi-Qiang Xia (20161326)

“…The aim was to affirm that MWOA-BiLSTM outperforms its counterparts, showcasing superior performance across crucial metrics such as accuracy, precision, recall, and F1-Score. …”

MOEA/D-ND algorithm flowchart. by Jun Sun (48981)

“…Its overall comprehensive performance is better than the comparison algorithm, and compared to the comparison algorithm, it converges more quickly in the early stage of iteration on 1 and 2, and tends to stabilize in the 40th generation, and completes convergence in the 80th generation. …”

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

Values of the objective function and its non-normalized terms , obtained by using different weights in the optimization process. by Roberto Castro-Medina (21484990)

Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

Comparative analysis of algorithms. by Xumin Zhao (18261643)

“…Notably, the LIRU algorithm registers a 5% increment in one-hop hit ratio relative to the LFU algorithm, a 66% enhancement over the LRU algorithm, and a 14% elevation in system hit ratio against the LRU algorithm. …”

Mean training time of different algorithms. by Wei Liu (20030)

“…The convergence of SGWO was analyzed by mathematical theory, and the optimization ability of SGWO and the prediction performance of SGWO-Elman were examined using comparative experiments. The results show: (1) the global convergence probability of SGWO was 1, and its process was a finite homogeneous Markov chain with an absorption state; (2) SGWO not only has better optimization performance when solving complex functions of different dimensions, but also when applied to Elman for parameter optimization, SGWO can significantly optimize the network structure and SGWO-Elman has accurate prediction performance.…”

Algorithm ranking under different dimensions. by Wei Liu (20030)

“…The convergence of SGWO was analyzed by mathematical theory, and the optimization ability of SGWO and the prediction performance of SGWO-Elman were examined using comparative experiments. The results show: (1) the global convergence probability of SGWO was 1, and its process was a finite homogeneous Markov chain with an absorption state; (2) SGWO not only has better optimization performance when solving complex functions of different dimensions, but also when applied to Elman for parameter optimization, SGWO can significantly optimize the network structure and SGWO-Elman has accurate prediction performance.…”

Compare algorithm parameter settings. by Yuqi Xiong (12343771)

“…Experimental validation shows that on 23 benchmark functions and the CEC2022 test suite, MESBOA significantly outperforms the original Secretary Bird Optimization Algorithm (SBOA) and other comparative algorithms (such as GWO, WOA, PSO, etc.) in terms of convergence speed, solution accuracy, and stability. …”

Flowchart of the specific incarnation of the BO algorithm used in the experiments. by Lisa Laux (9367681)

“…To choose the next pipeline configuration to evaluate, the BO algorithm uses an Expected Improvement function to trade off maximisation of QS with the need to fully learn the GP. …”

Brief sketch of the quasi-attraction/alignment algorithm. by Takayuki Niizato (162226)

“…(B) A sketch of the cover function, which returns the minimum cap on the interaction sphere , which covers all points <b><i>p</i></b>_<i>i</i> (for the mathematical definition, see the Section 2 in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010869#pcbi.1010869.s008" target="_blank">S1 Appendix</a>). …”

Flowchart of P&O-based MPPT algorithm. by Luqman Khan (17921419)

Description of unimodal benchmark functions. by Yi-Qiang Xia (20161326)

“…The aim was to affirm that MWOA-BiLSTM outperforms its counterparts, showcasing superior performance across crucial metrics such as accuracy, precision, recall, and F1-Score. …”

Description of multimodal benchmark functions. by Yi-Qiang Xia (20161326)

“…The aim was to affirm that MWOA-BiLSTM outperforms its counterparts, showcasing superior performance across crucial metrics such as accuracy, precision, recall, and F1-Score. …”

Statistical results of various algorithms. by ZeSheng Lin (20501356)

“…Secondly, the WOA’s position update formula was modified by incorporating inertia weight <i>ω</i> and enhancing convergence factor <i>α</i>, thus improving its capability for local search. …”

Images of partial benchmark functions. by ZeSheng Lin (20501356)

“…Secondly, the WOA’s position update formula was modified by incorporating inertia weight <i>ω</i> and enhancing convergence factor <i>α</i>, thus improving its capability for local search. …”

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”

WSN optimized by different algorithms. by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

Compare algorithm parameter settings. by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

DataSheet1_Mathematical algorithm–based identification of the functional components and mechanisms in depression treatment: An example of Danggui-Shaoyao-San.docx by Wenxia Gong (13277883)

“…In this study, we designed a novel strategy to capture the functional components and mechanisms of TCM based on a mathematical algorithm. …”