Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams حسب Eduardo Feo-Flushing (23276023)

"…Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. …"

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

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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method حسب 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. …"

CoLoSSI: Multi-Robot Task Allocation in Spatially-Distributed and Communication Restricted Environments حسب Ishaq Ansari (22047902)

"…<p dir="ltr">In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consist of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. …"

Predict Student Success and Performance factors by analyzing educational data using data mining techniques حسب 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 حسب 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. …"

Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data حسب 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 حسب 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 حسب 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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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices حسب Khawam, Yahya Bader

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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation حسب 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 combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators حسب Al-Hamouz, Z.M.

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

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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification حسب Rajendra Babu Chikkala (22330876)

"…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …"

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms حسب 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 حسب Kamalov, Firuz

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Using Machine Learning Algorithms to Forecast Solar Energy Power Output حسب 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 حسب 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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A reduced model for phase-change problems with radiation using simplified PN approximations حسب Belhamadia, Youssef

"…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …"
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network حسب 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). …"