Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple tea fields.XLSX by Yangyang Liu (807797)

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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Illustration of crossover. by Ruochen Zhang (3434996)

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

Parameter settings of the comparison algorithms. by Ying Li (38224)

“…<div><p>Feature selection is an important solution for dealing with high-dimensional data in the fields of machine learning and data mining. In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”

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

“…<div><p>Feature selection problem represents the field of study that requires approximate algorithms to identify discriminative and optimally combined features. …”

Parameter settings. by Olaide N. Oyelade (14047002)

“…<div><p>Feature selection problem represents the field of study that requires approximate algorithms to identify discriminative and optimally combined features. …”

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

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IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

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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Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

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

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)

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