MEA-BP neural network algorithm flowchart. by Dongling Ma (1269888)

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Pseudocode for the CORDIC algorithm to compute multiplication. by Mehdi Nadiri Andabili (22097275)

Comparison of optical and silicon-based neural network implementations. by Reyhane Ahmadi (14857363)

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Comparison of power consumption in optical and silicon-based neural network implementations. by Reyhane Ahmadi (14857363)

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Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.…”

The machine learning framework implemented in the present work. by Akshansh Mishra (21001499)

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Choices on individual test tasks were not explained by model-free perseveration. by Sam Hall-McMaster (10343795)

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Coati optimization algorithm for brain tumor identification based on MRI with utilizing phase-aware composite deep neural network by Rajesh Kumar Thangavel (20591164)

“…In this research, Utilizing Phase-aware Composite Deep Neural Network Optimized with Coati Optimized Algorithm for Brain Tumor Identification Based on Magnetic resonance imaging (PACDNN-COA-BTI-MRI) is proposed. …”

Supervised Predictive Modeling of High-dimensional Data with Group l0-norm Constrained Neural Networks by Zhihuang Yang (22530437)

“…Moreover, two iterative greedy selection algorithms, which iterate between a standard gradient descent step and a hard thresholding step with or without debiasing, are presented to implement the computation. …”

MEA-BP neural network training process curve. by Dongling Ma (1269888)

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Convergence curve of the DBO algorithm. by Ma Haohao (22177538)

“…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”

Data and Scripts for 'A Predictive Model for Attention-deficit/hyperactivity Disorder and Its Subtypes in Children: A Back-propagation Neural Network Optimized with Genetic Algorithms Based on Multidimensional Cognitive Ability Tests' by Wang (20310746)

“…Using <a href="" target="_blank">multidimensional cognitive ability tests</a> and a <a href="" target="_blank">back-propagation neural network</a> optimized by a genetic algorithm, this study developed a computer-aided diagnostic model to distinguish children with attention-deficit/hyperactivity disorder and its specific subtypes. …”

Data and Scripts for 'Application of Multidimensional Cognitive Ability Tests in Computer-Assisted Diagnosis of Attention-Deficit/Hyperactivity Disorder and Its Subtypes in Children: Based on A Genetic Algorithm Optimized Back-Propagation Neural Network Predictive Model' by Wang (20310746)

“…Using <a href="" target="_blank">multidimensional cognitive ability tests</a> and a <a href="" target="_blank">back-propagation neural network</a> optimized by a genetic algorithm, this study developed a computer-aided diagnostic model to distinguish children with attention-deficit/hyperactivity disorder and its specific subtypes. …”

Machine learning prediction algorithm flow chart. by Ahmad M. Al-Omari (20460931)

Data and code resources. by Sam Hall-McMaster (10343795)

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Experimental design. by Sam Hall-McMaster (10343795)

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Behavioral results. by Sam Hall-McMaster (10343795)

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Choice behavior on individual test tasks. by Sam Hall-McMaster (10343795)

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Parameter configuration for ChildEmoNet algorithm implementation. by Zhang Shanshan (22272359)

Cloud model evaluation values for each indicator. by Dongling Ma (1269888)

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