Fragment-based computational protein structure prediction by Mansour, Nashat

“…The method is based on a two-phase Scatter Search algorithm that minimizes the energy function. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”

Fragment based protein structure prediction. (c2013) by Terzian, Meghrig Ohanes

“…This work presents a fragment based protein tertiary structure prediction method that provides suboptimal structures. …”
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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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Towards Multimedia Fragmentation by Saad, Samir

“…In this paper, we address multimedia database fragmentation by extending existing fragmentation algorithms to take into account key characteristics of multimedia objects. …”
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The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation by Getahun, Fekade

“…We particularly discuss multimedia primary horizontal fragmentation and focus on semantic-based textual predicates implication required as a pre-process in current fragmentation algorithms in order to partition multimedia data efficiently. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”

Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers by Yousef, Hibba

“…In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. …”
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Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... by Elmahdy, Samy

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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
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Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Developing a UAE-Based Disputes Prediction Model using Machine Learning by Abu Laila, Ibrahim Wasef Subhi

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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

“…These algorithms include random forest (RF) classification and artificial neural networks (ANN). …”

Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine by Shomope, Ibrahim

“…In this regard, Random Forest (RF) and Support Vector Machine (SVM) are two ML algorithms that have been extensively applied in various biomedical and drug delivery contexts. …”
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Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…Therefore, in this paper we propose the usage of historical charging data in conjunction with weather, traffic, and events data to predict EV session duration and energy consumption using popular machine learning algorithms including random forest, SVM, XGBoost and deep neural networks. …”
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation by Khaled Dhibi (16891524)

“…In the proposed FDD approach, named interval reduced kernel PCA (IRKPCA)-based Random Forest (IRKPCA-RF), the feature extraction and selection phase is performed using the IRKPCA models while the fault classification is ensured using the RF algorithm. …”

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

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