A Comprehensive Review on Conventional and Machine Learning-Assisted Design of 5G Microstrip Patch Antenna by Nupur Chhaule (21224987)

Graph Computing Systems and Partitioning Techniques: A Survey by Tewodros Alemu Ayall (19273717)

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Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic by Hassan Farhat (9000509)

“…</p><h3>Methods</h3><p dir="ltr">Using Python® programming language, this study employed various supervised machine-learning algorithms, including parametric probabilistic models, such as logistic regression, and non-parametric models, including decision trees, random forest (RF), extra trees, AdaBoost, and k-nearest neighbours (KNN), using a dataset of non-transported patients (refused transport and did not receive treatment versus those who refused transport and received treatment) between 2018 and 2022. …”

A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

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Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms by Emara-Shabaik, Husam

“…In this paper, a modified genetic algorithm is used as a procedure to solve the parameter identification problem of the nonlinear Wiener-Hammerstein models. …”
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A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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Combining and adapting software quality predictive models by genetic algorithms by Azar, D.

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Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

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Optimization of Piezoelectric Sensor-Actuator for Plate Vibration Control Using Evolutionary Computation: Modeling, Simulation and Experimentation by Asan G. A. Muthalif (16888818)

“…Both disturbance and control signal acting on the plate is created by using piezoelectric (PZT) patches. The analytical model is derived based on the Euler-Bernoulli model. …”

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

“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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Gas Metal Arc Welding (GMAW) Process Optimization Using Machine Learning Models by Sharaf, Ahmed

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Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

“…The low R-squared scores obtained by the models are likely to be due to the low resolution of the NHANES data, particularly the dietary data. …”

UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”

Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation by Fawaz Kserawi (16904859)

“…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…The values are 18.44 % and 23.9 % for CV-RMSE, 11.6 % and 10.06 % for MAPE, and 7.5 % and 6.75 % for MdAPE, using ANN and GP, respectively. While the previous studies mostly used ANN to demonstrate the capability of MLs to predict PG over the mechanistic or correlation-based models, the present research has shown that GP is even better than ANN using a wide range of FPs and a large data set.…”

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

WiMAX Models for the Smart Grid by Al-Omar, Ban Abdul Elah

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Nonlinear model predictive control of Hammerstein and Wiener modelsusing genetic algorithms by Al-Duwaish, H.

“…In this paper a novel approach for the implementation of nonlinear MPC is proposed using genetic algorithms (GAs). The proposed method formulates the MPC as an optimization problem and genetic algorithms are used in the optimization process. …”
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A method for data path synthesis using neural networks by Harmanani, H.

“…Presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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