Binary B-Hill Climbing Optimizer with S-shape Transfer Function for Feature Selection by Abou Doush, Iyad

“…In this paper, a β β -hill climbing optimizer is applied to solve the feature selection problem. β β -hill climbing is recently introduced as a local-search based algorithm that can obtain pleasing solutions for different optimization problems. …”
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Nonlinear clustering optimization for scalable data mining in cloud and quantum computing environments by Manjula, S.

“…The approach combines the dynamical systems analysis, PDE-based manifold models and quantum optimization mappings (QUBO/Ising), which ensure the theoretical soundness of the approach; specifically, the approach is coercive, has minimizers, and block-coordinate convergence guarantees. …”
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An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks by Md Moktadir Rahman (16904751)

“…An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. …”

A modified optimal design of a vibration absorber for ground motion isolation by Issa, Jimmy S.

“…The first is based on the genetic algorithm technique and the second on the downhill simplex method. …”
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Optimal location and sizing of renewable distributed generations and electric vehicle charging stations by Guindi, Marina

“…The study introduces several constraints, including the placement of EVCSs and RDGs at separate buses, and employs particle swarm optimization and cuckoo search algorithm to simultaneously determine the optimal locations and sizes of the RDGs and the optimal locations of the EVCSs. …”
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Hybrid quantum–cloud framework for nonlinear clustering optimization and intelligent resource management by Abdullayev, Ilyos

“…These weaknesses will be mitigated by the proposed framework that will integrate quantum-inspired algorithms (which will operate on variational quantum circuits and Quantum Approximate Optimization Algorithm (QAOA)) with cloud-native orchestration solutions, only that reinforcement learning-based scheduling will be integrated. …”
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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review by Mohamed Sadok Massaoudi (17984071)

“…<p dir="ltr">The widespread penetration of inverter-based resources has profoundly impacted the electrical stability of power systems (PSs). …”

Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace by Shahid, Saif Mohammad

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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…This study offers a thorough examination of how AI can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”

Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks by Amirhossein Taherpour (19273879)

“…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …”

Learning-Based Automatic Modulation Classification by Abdelmutalab, Ameen Elsiddig

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Particle swarm optimization approach for protein structure prediction in the 3D HP model by Mansour, Nashat

“…In this paper, we present a particle swarm optimization (PSO) based algorithm for predicting protein structures in the 3D hydrophobic polar model. …”
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LOCATING DAMAGES IN THIN ALUMINIUM PLATES USING LAMB WAVES AND AGENETIC OPTIMIZATION APPROACH by A. Masurkar, Faeez

“…A new damage localization method based on Lamb waves is presented here for thin aluminium (Al) plate specimens using a Genetic optimization (GO) approach. …”
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Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks by Mohamed Massaoudi (16888710)

“…<p dir="ltr">The transient power grid stability is greatly affected by the unpredictability of inverter-based resources of today's interconnected power grids. …”

The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability by Abd-El-barr, Mostafa

“…In this paper, we propose one algorithm for optimizing the terminal reliability and another for optimizing the network reliability while improving the fault tolerance aspects of the designed networks. …”
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Enhanced Microgrid Reliability Through Optimal Battery Energy Storage System Type and Sizing by Mohammadreza Gholami (17032317)

“…To determine the optimized size, a firefly optimization algorithm is used as an efficient meta-heuristic approach. …”

A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability by Debabrata Mazumdar (18560506)

“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”

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

“…The model aims to compare the performance of classical perturb and observe (P&O) algorithm, particle swarm optimization (PSO) algorithm, flower pollination algorithm (FPA), and SMC-based tracking techniques. …”
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Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…In this thesis, we propose a novel heuristic based on Artificial Bee Colony (ABC) to optimize rule-based software quality prediction models. …”
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Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. …”