Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by Odat, Alhaj-Saleh A.

“…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …”
Get full text
Get full text
Get full text

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 Low-Cost Closed-Loop Solar Tracking System Based on the Sun Position Algorithm by E. H. Chowdhury (545276)

“…In summary, even for a small-scale solar tracking system, the algorithm-based closed-loop dual-axis tracking system can increase overall system efficiency. …”

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. …”
Get full text

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

“…The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …”
Get full text

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

Subjects:

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

Get full text

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. …”
Get full text

Detecting sleep outside the clinic using wearable heart rate devices by Ignacio Perez-Pozuelo (14153007)

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. …”
Get full text

Tracking and repairing damaged healthcare databases using the matrix by Haraty, Ramzi A.

Get full text
Get full text
Get full text
Get full text

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). …”

Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las... by Masurkar, Faeez

“…The functioning of the algorithm was successfully tested by carrying out extensive experiments on a real rail track in the presence of different types of surface and sub-surface defects on its head and web. …”
Get full text

Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea by Issa, Leila

“…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …”
Get full text
Get full text
Get full text
Get full text

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. …”
Get full text

A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants by Khan, T.

“…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …”
Get full text
Get full text

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. …”