AI-driven nonlinear optimization for knowledge extraction and pattern analysis in IoT-enabled data mining systems حسب Alimjon, Dadamuxamedov

"…The paper explains the complexity and heterogeneity of IoT data on scale by declaring and resolving nonlinear optimization problems using the latest AI methods, including genetic algorithms and neural networks. …"
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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation حسب Said Mahfoud (17150968)

"…The best solutions adopted in this situation are often based on optimization algorithms that generate the controller’s gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system’s nonlinearity. …"

An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models حسب K. Mukilan (22224793)

"…The Monarch Butterfly Optimization Algorithm (MBOA) and its improved version (IMBOA) are explored for their application in optimizing project performance. …"

An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure حسب Fahmy, Ahmed

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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities حسب Mahdi Mokhtarzadeh (11593310)

"…To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …"

Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach حسب El Gohary, Youssef Hesham

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Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures حسب JUMA, MAZEN GHAZI

"…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …"
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Optimum Partition of Power Networks Using Singular Value Decomposition and Affinity Propagation حسب Maymouna Ez Eddin (21633650)

"…From this perspective, this paper proposes an efficient framework for fast and optimal PGP, based on singular value decomposition analysis of the graph's Laplacian. …"

An optimization approach to increasing sustainability and enhancing resilience against environmental constraints in LNG supply chains: A Qatar case study حسب Sara Al-Haidous (18095368)

"…The developed model, which is implemented using the Binary Particle Swarm Optimization algorithm subjected to economic and environmental objectives within an overarching strategic aim for sustainability and resilience. …"

A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System حسب Ekinci, Serdar

"…We show the CmOBL-AO algorithm to perform better than the differential evolution algorithm, gravitational search algorithm, African vultures optimization, and the Aquila Optimizer using well-known unimodal, multimodal benchmark functions. …"
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Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP حسب Abdelhafez, Nada

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Metaheuristic Optimization‐Based Sliding Mode Control With Modified Perturb and Observe for Controlling MPPT of a PV Interfaced Grid Connected System حسب Anupama Ganguly (22502969)

"…Also, this article introduces the meta‐heuristic algorithm mountain gazelle optimization (MGO), which is incorporated to optimize the parameters of the sliding mode controller (SMC) to ensure the solar PV (SPV) MPP extraction. …"

Net energy–cost optimization of STPV–PDRC integrated greenhouses: Balancing energy production and cooling demand under crop-specific DLI constraints حسب Mohammadreza Gholami (17032317)

"…An improved equilibrium optimizer (IEO) algorithm was employed to solve the multi-objective problem. …"

Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids حسب Khayata, Mohammad Tarek

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A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems حسب Kandil, Sarah M.

"…The formulation employs a general objective function that optimizes the total Annual Cost of Energy (ACOE). …"
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Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach حسب Haitham Osman (11737057)

"…<p>This paper presents the design, modeling, and multi-objective optimization of an advanced solar energy system based on concentrated solar power technology, aimed at sustainable electricity generation in urban environments. …"

A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand حسب Khawar Naeem (17984062)

"…The models included agent-based modeling (ABM), Bayesian networking (BN), analytical hierarchy approach (AHP), and simulation optimization multi-objective optimization (MOO). The solution approaches included the genetic algorithm (GA), particle swarm optimization (PSO), and the non-dominated sorting genetic algorithm (NSGA-II). …"

Software defect prediction. (c2019) حسب Moussa, Rebecca

"…One that focuses on predicting defect in software modules using a hybrid heuristic - a combination of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). We compare our approach to 9 well known machine learning techniques and results show the advantages of our model over the other techniques. …"
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DRL-Based IRS-Assisted Secure Visible Light Communications حسب Danya A. Saifaldeen (19498705)

"…The DDPG-based algorithm provides an optimized solution that can adapt to the large size of design parameters and act fast to the channel variations due to users’ mobility. …"

Reinforcement Learning for Resilient Aerial-IRS Assisted Wireless Communications Networks in the Presence of Multiple Jammers حسب Zain Ul Abideen Tariq (17984107)

"…Hence, we leverage the light-weight Deep Reinforcement Learning (DRL) technique called Deep Deterministic Policy Gradient (DDPG) to optimize trajectory and IRS phase shifts and achieve multiple objectives jointly. …"