Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…<p dir="ltr">Machine learning (ML) frameworks are transforming the development of corrosion inhibitors by enabling quantitative prediction of inhibition efficiency before synthesis. …”

Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

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Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”

Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems by Mahmood, Lubna Syeda

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Machine learning approach for the classification of corn seed using hybrid features by Aqib Ali (19680145)

“…The purpose of this study was to examine the feasibility of a machine learning (ML) approach for classifying different types of corn seeds. …”

Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

“…Each user participated in 500 trials at 10 different sessions (days) to replicate real-life signal variability. A machine learning classification pipeline is developed using multi-domain feature extraction (time, frequency, time-frequency), feature selection (Gini impurity), classifier design, and score level fusion. …”

Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm by Khadija Attouri (18024307)

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Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

“…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”

An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm by Ghulam Jillani Ansari (16896342)

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Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

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Enhancing fairness and scalability in IOTA tangle networks: a POMDP-based tip selection algorithm for decentralized systems by Mays Alshaikhli (22564811)

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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”

A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model by Md. Nazmul Islam Shuzan (16888827)

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Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

“…Federated Learning (FL) is a novel distributed privacy-preserving learning paradigm, which enables the collaboration among several participants (e.g., Internet of Things devices) for the training of machine learning models. …”
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Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems by Amal Hichri (21383672)

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