Pseudocode of the BBAC_I Algorithm. by Zezhi Lin (22521663)

Execution Steps of the EOF Algorithm. by Zezhi Lin (22521663)

Algorithm flow of BBO. by Jian Yang (12136)

“…<div><p>The stable and site-specific operation of transmission lines is a crucial safeguard for grid functionality. This study introduces a comprehensive optimization design method for transmission line crossing frame structures based on the Biogeography-Based Optimization (BBO) algorithm, which integrates size, shape, and topology optimization. …”

2lpiRNApred: a two-layered integrated algorithm for identifying piRNAs and their functions based on LFE-GM feature selection by Yun Zuo (8541492)

“…A new feature selection algorithm, which was based on Luca fuzzy entropy and Gaussian membership function (LFE-GM), was proposed to reduce the dimensionality of the features. …”

Results of each algorithm. by Guilin Yang (583364)

“…To evaluate the performance of the proposed algorithm, 27 well-known test reference functions were selected for experimentation, which showed significant advantages compared to other algorithms. …”

Smoothing curve from GAM model in which the survival of smaller cluster has been modeled as a smooth function of the sample size. by Muhammad Atif (2575789)

Smoothing curve from GAM model in which the survival of smaller cluster has been modeled as a smooth function of the sample size. by Muhammad Atif (2575789)

Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)

Membership function of each target. by Tianrui Zhang (2294542)

“…Experimental results show that the PSCACO algorithm proposed in this paper is compared with MOPSO, CACO and NSGA-II algorithms, and the convergence effect of the algorithm is concluded to be more effective to verify the effectiveness and feasibility of chaotic particle ant colony algorithm for solving multi-objective functions, which proposes a new feasible solution for the supply chain management.…”

Adding a new function module. by Yukako Yamane (9034133)

Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Feature selection algorithm. by Mahmoud Zeydabadinezhad (12289570)

“…Electrogastrography (EGG), which measures gastric electrical activities (GEAs) as a proxy to quantify GI functions, was employed in our investigation. …”

Imperialist competition algorithm with quasi-opposition-based learning for function optimization and engineering design problems by Dongge Lei (6836915)

“…To address these issues, an improved ICA is proposed by combining ICA with a quasi-opposition-based learning (QOBL) strategy, which is named QOBL-ICA. …”

Auscultation locations for the CirCor DigiScope dataset [6], which was used for the Challenge: Pulmonary valve (PV), aortic valve (AV), mitral valve (MV), and tricuspid valve (TV). by Matthew A. Reyna (16965038)

Test function results. by Ruyi Dong (9038174)

“…In addition, to verify the performance and robustness of LLSKSO, comparison experiments between LLSKSO and 10 well-known algorithms are conducted on 50 benchmark test functions. …”

Benchmark test functions. by Ruyi Dong (9038174)

“…In addition, to verify the performance and robustness of LLSKSO, comparison experiments between LLSKSO and 10 well-known algorithms are conducted on 50 benchmark test functions. …”

The details of the test algorithm. by Yule Sun (16015342)

“…<div><p>A deep memory bare-bones particle swarm optimization algorithm (DMBBPSO) for single-objective optimization problems is proposed in this paper. …”

Boxplot of fitness in various algorithms. by Wei Liu (20030)

“…We proposed an improved grey wolf optimizer (SGWO) to explore a better network structure. GWO was improved by using circle population initialization, information interaction mechanism and adaptive position update to enhance the search performance of the algorithm. …”

Variations in the effectiveness and cost of the eight Ebola screening algorithms as a function of the prevalence of Ebola virus disease in the suspected population. by Antoine Oloma Tshomba (14271425)

Table_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.DOCX by Shakiru A. Alaka (9302864)

“…<p>Background and Purpose: Stroke-related functional risk scores are used to predict patients' functional outcomes following a stroke event. …”