A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

Illustration of the BRIDES algorithm and the selection process. by Cindy Bouchard (6844979)

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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…This strategy </p><p dir="ltr">not only improves detection efficiency and accuracy but also supports early diagnosis and treatment planning, </p><p dir="ltr">leading to better patient outcomes. By leveraging the binary GWO algorithm to optimize the feature selection </p><p dir="ltr">process and CNNs for image classification, the proposed approach reduces computational costs while increasing </p><p dir="ltr">classification accuracy. …”

Illustration of crossover. by Ruochen Zhang (3434996)

Datasets and their properties. by Olaide N. Oyelade (14047002)

“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”

Parameter settings. by Olaide N. Oyelade (14047002)

“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”

Sampled population parameters and corresponding node-based metrics, node removal statistics and BRIDES results. by Cindy Bouchard (6844979)

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Population graph of 19 wood turtle populations based on conditional genetic distance (cGD). by Cindy Bouchard (6844979)

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Different population subgraphs based on distinct node selection parameters using a proactive or reactive conservation approach. by Cindy Bouchard (6844979)

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Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

“…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …”

The AD-PSO-Guided WOA LSTM framework. by Ahmed M. Elshewey (21463867)

“…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …”

Prediction results of individual models. by Ahmed M. Elshewey (21463867)

“…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …”

Results of the BRIDES node selection procedure for two scenarios and three weighted models. by Cindy Bouchard (6844979)

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BRIDES node selection process for scenario Ap and Model B³D¹E²S³ (3, 0, 0, 1, 2, 3). by Cindy Bouchard (6844979)

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Summary of the BRIDES node selection procedure providing the minimum number of nodes required to reach a maximal score, and the number of multiple solutions with the same score for... by Cindy Bouchard (6844979)

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WGCNA analysis and construction of a prognostic risk score based on CXCL9 + macrophage-related genes. by Bin Liang (228729)

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

Subset lattices with parent set constraints and best sinks identified by CausNet-partial as an example. by Nand Sharma (21519845)

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

“…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …”

DataSheet1_CD8TCEI-EukPath: A Novel Predictor to Rapidly Identify CD8+ T-Cell Epitopes of Eukaryotic Pathogens Using a Hybrid Feature Selection Approach.docx by Rui-Si Hu (5337227)