Radar Pulse Interleaving For Multi-Target Tracking by Elshafei, M.

“…Interleaving algorithms developed to operate radars exploit the dead-times between the transmitted and the received pulses to allocate new tracking tasks that might involve transmitting or receiving pulses, thus increasing the capacity of the system. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

“…This paper presents two different methods for track-to-track fusion of drone tracks. The sensors are unbiased radars with fixed locations. …”
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Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization by Alhadhrami, Esra Ebrahim

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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem by Abu Zitar, Raed

“…In many cases, several radars are collectively used to track drones efficiently, generating measurements and several tracks under different circumstances. …”
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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. …”

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. …”

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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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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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. …”

Analyzing the Influence of Climate and Anthropogenic Development on Vegetation Cover in the Coastal Ecosystems of GCC by Abhilash Dutta Roy (22466830)

“…We used Landsat satellite imagery and a Random Forest classification algorithm to map various land cover classes along the GCC coastline. …”

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

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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

“…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …”
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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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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). …”

Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…In this work, one radar and one camera collaborate to generate tracks of a drone. …”
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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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A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies by Farideh Abdollahi (22303153)

“…The fingerprinting and descriptors are two commonly approach for polymer featurization. In terms of algorithms, <u>neural networks</u> (NNs), random forest (RF), and gaussian process regression (GPR) are among the most extensively applied methods. …”

Anomaly Detection Based Framework for Profile Monitoring by Al-Rahim, Nour Al-Huda Z. Al-Abed

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