Convergence curve of others functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

Convergence curve of multimodal functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

Convergence curve of multimodal functions compared with the PSO family algorithms. by Yong Gao (29929)

<b>The Negative Digital Root Implemented as a Mathematica Standalone Function</b> by Paul F. Marrero Romero (17450601)

<b>Gene Catalog and Associated Functional Data</b> for BioProject PRJNA1311452 by Satheeswaran Thangaraj (22187269)

Conservation and functional variation across TcdB subtypes. by Michael J. Mansfield (9922934)

Experiment 1b: Evaluating modularity-based consensus clustering pipelines on the algorithm design datasets as a function of the mixing parameter. by Yasamin Tabatabaee (18095491)

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space by Koushik Naskar (7510592)

“…The “ADT” program can be efficiently used to (a) formulate analytic functional forms of differential equations for ADT angles and diabatic potential energy matrix and (b) solve the set of coupled differential equations numerically to evaluate ADT angles, residue due to singularity­(ies), ADT matrices, and finally, diabatic potential energy surfaces (PESs). …”

Pipeline of the interactor algorithm. by Jose Cleydson F. Silva (8685594)

Line charts of the elbow method and the k-value selection algorithm: (A) elbow method; (B) k-value selection algorithm. by Jingnan Yan (20727331)

CPU runtime of each algorithm: (a) Running Time Comparison of Different Algorithms on F1-F10 and (b) Running Time Comparison of Different Algorithms on F11-F20. by Ruyi Dong (9038174)

Flowchart of proposed algorithm. by Tibebu Legesse (21030014)

“…Moreover, the proposed algorithm significantly extends network lifetime, with a <b>3.5%</b> and <b>7.5%</b> improvement over EAPS-AODV and AODV. …”

The SSIM for the different algorithms. by Bingbing Li (461702)

“…Unlike traditional threshold functions, the improved threshold function is a continuous function that can avoid the pseudo Gibbs effect after image denoising and improve image quality. …”

Skeletonisation algorithm. by Jordan Hembrow (16908051)

The execution times (nano seconds) per particle are measured for four different algorithms [47], (A: first algorithm, B: second algorithm, C: third algorithm: and D: fourth algorit... by Abedalmuhdi Almomany (18547669)

(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms. by Ruyi Dong (9038174)

“…<p>Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms.…”

Gene function enrichment analysis: GO function enrichment analysis (A) and KEGG pathway enrichment analysis (B). by Yaling Hu (11648397)

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by Pascal Wang (10130612)

“…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …”