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

“…Numerical simulations are presented to illustrate the effectiveness of the proposed algorithm based on different input signals, and different noise-to-signal ratios of the output. …”
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An efficient method for the open-shop scheduling problem using simulated annealing by Harmanani, Haidar M.

“…The method is based on a simulated annealing algorithm that efficiently explores the solution space. …”
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems by Devinder Kaur (264278)

A new minimum curvator multi-step method for unconstrained optimization by Obeid, Samir

“…Our derivation of the new algorithm is based on determining some value of the parameter that minimizes the curvature in some chosen metric. …”
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An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

“…Textual data contains much useless information that must be pre-processed. …”

Bee colony algorithm for assigning proctors to exams. (c2013) by Taha, Mohamad Kassem

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An incremental approach for test scheduling and synthesis using genetic algorithms by Harmanani, H.

“…The method is based on a genetic algorithm that efficiently explores the testable design space. …”
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms by Harmanani, H. M.

“…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …”

Power Control Algorithms for Media Transmission in Remote Healthcare Systems by Ali Hassan Sodhro (18629392)

“…Thus, this paper first proposes a transmission power control (TPC)-based energy-efficient algorithm (EEA) for when a subject is in different postures, i.e., standing, walking, and running, in wireless body sensor networks. …”

Methods for system-on-chip test design, scheduling and optimization. (c2006) by Farah, Rana

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Dynamic Layout Planning Using a Hybrid Incremental Solution Method by Zouein, Pierrette

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Development of a cerebral aneurysm segmentation method to prevent sentinel hemorrhage by Yousra Regaya (17788964)

“…A robust brain aneurysm segmentation has the potential to prevent the blood leakage, also known as sentinel hemorrhage. Here, we present a method combining a multiresolution and a statistical approach in two dimensional domain to segment cerebral aneurysm in which the Contourlet transform (CT) extracts the image features, while the Hidden Markov Random Field with Expectation Maximization (HMRF-EM) segments the image, based on the spatial contextual constraints. …”

Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”

Combinatorial method for bandwidth selection in wind speed kernel density estimation by El Dakkak, Omar

“…In this study, a non-parametric combinatorial method is implemented for obtaining an accurate non-parametric kernel density estimation (KDE)-based statistical model of wind speed, in which the selection of the bandwidth parameter is optimised concerning mean integrated absolute error (L 1 error ) between the true and hypothesised densities. …”
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Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring by Sakib Mahmud (15302404)

“…<h3>Background and Motivations</h3><p dir="ltr">Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”

Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles by Zainab Akhtar (15192184)

“…<p dir="ltr">The control and state estimation of Unmanned Aerial Vehicles (UAVs) provide significant challenges due to their complex and nonlinear dynamics, as well as uncertainties arising from factors such as sensor noise, wind gusts, and parameter fluctuations. Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. …”

Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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Convergence and steady-state analysis of the normalized least mean fourth algorithm by Zerguine, Azzedine