A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators by Al-Hamouz, Z.M.

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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. 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. …”

Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

“…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
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A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari (22467148)

“…A range of machine learning (ML) methods can be used to recognize facial expressions based on data from small to large datasets. Random Forest (RF) is simpler and more efficient than other ML algorithms. …”

Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

“…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …”

A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48 by Al-Manaseer, Hitham

“…This was done by studying the performance of three well-known classification algorithms Random Forest Classifier (RFC), Support Vector Machine (SVM), and Decision Tree-J48 (J48), to predict the probability of heart attack. …”
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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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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars by Abathar Al-Hamrani (16494884)

“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V_pred/V_exp) ratio of 0.97 and a coefficient of variation of 17.91%.…”

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. …”

Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch (17983846)

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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms by Usman Ali (6586886)

“…Extracted vegetation indices were evaluated on three ML algorithms, namely, random forest (RF), k-nearest neighbour (K-NN), and k dimensional-tree (KD-Tree). …”

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

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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. …”

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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On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

“…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …”

A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

“…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”

Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques by Abdul Karim (417009)

“…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”

Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices by Khawam, Yahya Bader

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