Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

“…However, the traditional AOA faces some limitations in its search process. Thus, we develop a new variant of the AOA, namely, Augmented AOA (AAOA), integrated with the opposition-based learning (OLB) and Lévy flight (LF) distribution. …”

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

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Random vector functional link network: Recent developments, applications, and future directions by A.K. Malik (16003193)

“…RVFL model has several characteristics such as fast training speed, direct links, simple architecture, and universal approximation capability, that make it a viable randomized neural network. …”

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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Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

“…These results outperform the individual modalities with a significant margin (~5%). We also developed a binary template matching-based algorithm, which gives 93.64% accuracy 6X faster. …”

Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery by Al Rayes, Zaid

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Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

“…Looking at the historical data of students, fuzzy logic can be used to develop rules based on these data. Genetic Algorithm would be used to optimize the performance of the system.…”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”

Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem by Nezir Aydin (8355378)

“…We present the effectiveness of the developed integrated approaches, Sampling Based Progressive Hedging Algorithm (SBPHA) and Discarding SBPHA (d-SBPHA), over the pure strategies (i.e. …”

Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm by Abraham Marquez Alcaide (18582451)

“…<p dir="ltr">Hand-in-hand with the smart-grid paradigm development, power converters used in high-power applications are facing important challenges related to efficiency and power quality. …”

Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study by Alkhodari, Mohanad Ahmed

“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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Neural Networks as a Convex Problem by Khalil, Baha

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

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Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

“…<p>Resistance to differential cryptanalysis is a fundamental security requirement for symmetric block ciphers, and recently, deep learning has attracted the interest of cryptography experts, particularly in the field of block cipher cryptanalysis, where the bulk of these studies are differential distinguisher based black-box attacks. This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”

Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems by Amal Hichri (21383672)

“…Tools for feature extraction and selection and fault classification are applied in the developed FDD approach to monitor the GCPV system under various operating conditions. …”

Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends by Abdellatif M. Sadeq (16931841)

“…The k-fold cross-validation technique is used for model training, and the developed neural network-based model is used to investigate the effects of operating parameters on the premixed turbulent flames. …”

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

“…We developed and tested a heart rate-based algorithm that captures inter- and intra-individual sleep differences in free-living conditions and does not require human input. …”