Small-scale dataset comparative analysis using computation resources. by Olaide N. Oyelade (14047002)

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Small-scale dataset comparative analysis using the number of features selected. by Olaide N. Oyelade (14047002)

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Large-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

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Parameter settings. by Olaide N. Oyelade (14047002)

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Fig 2 - by Olaide N. Oyelade (14047002)

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

“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. The A* algorithm then evaluated connectivity by minimizing Euclidean distance and heuristic cost between cells. …”

Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel (19843282)

DataSheet1_Improving the convergence of an iterative algorithm for solving arbitrary linear equation systems using classical or quantum binary optimization.pdf by Erick R. Castro (11243697)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Confusion matrix for a binary outcome (adapted from Fawcett [30]). by João Albuquerque (12936572)

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

Proposed Algorithm. by Hend Bayoumi (22693738)

“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”

The data processing and analysis pipeline. by Xin Zhang (35492)

Comparisons between ADAM and NADAM optimizers. by Hend Bayoumi (22693738)

“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”

Analysis and design of algorithms for the manufacturing process of integrated circuits by Sonia Fleytas (16856403)

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

The flowchart of the proposed algorithm. by Muhammad Ayyaz Sheikh (18610943)

“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”

Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)

The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... by Aninda Astuti (21736334)