Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

“…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …”

Classification algorithm implemented in SPARTA. by Baptiste Ruiz (20285217)

Comparison of different algorithms. by Dawei Wang (471687)

“…An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”

SpatialKNifeY analysis landscape. by Shunsuke A. Sakai (13789939)

Pseudo-code of DMDDPG algorithm. by Guohua Cao (697580)

“…Next, a reward function is designed by integrating the decoupled multi-agent deterministic deep deterministic policy gradient (DMDDPG) algorithm. …”

Convergence graphs of CEC2021 test functions. by Yu Liu (6938)

“…<div><p>The competition of tribes and cooperation of members algorithm (CTCM) is a novel swarm intelligence algorithm, which increases the diversity of the population to a certain extent through tribal competition and member cooperation mechanisms. …”

Depiction of how the label of is assigned as a function of whether are identical (row =), nested (rows ), or partially overlapping (row “else”), and as a function of the labels of... by Jordan Moutet (21800145)

Genetic algorithm flowchart. by Junjie He (700642)

“…Additionally, sensitivity analysis was conducted to explore the effect of different parameters on the maximum fire risk value that can be covered by a fire station. A compromise coordinated siting scheme with a hierarchy of fire stations can be obtained by solving the proposed model. …”

Algorithm Parameter Setting. by Tong Zhou (3770)

“…Therefore, an Improved Dueling Double DQN (D3QN) On-ramp Merging Strategy (IDS stands for the initials of Improved, D3QN, and Strategy) combined with a sine function is proposed, establishing a Vehicle Coordination System (VCS) to guide the merging of vehicles in multi-lane mainline traffic. …”

IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

IEEE CEC 2022 benchmark function specifications. by Kankan Tang (21474968)

Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm by Gelio Alves (51850)

“…To overcome this limitation, we implemented an expectation-maximization (EM) algorithm, along with a biological function database, within the MiCId workflow. …”

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

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.…”

The benchmark functions. by Shuhui Yu (1535500)

Benchmark functions. by Yun Qi (560401)

Study proposed algorithm. by Ainhoa Pérez-Guerrero (21377457)

“…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. …”

The training process for PV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

The training process for AV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

The training process for TV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)