Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm حسب 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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An Energy Efficient Wireless Sensor Network for Optimal Routing using Hybridized Bio-Inspired Technique حسب Askarovich, Ulashev Hubbim

"…While clustering techniques, such as Low Energy Adaptive Clustering Hierarchy (LEACH), help reduce energy usage, they suffer from inefficient local searches and poor exploration-exploitation balance.To address these limitations, this study proposes a hybrid bio-inspired optimization technique—Modified Harmony Search Algorithm (MHSA) combined with Competitive Swarm Optimization (CSO)—for optimal cluster head (CH) selection. …"
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A Novel Link-based Multi-objective Grey Wolf Optimizer for Appliances Energy Scheduling Problem حسب Abou Doush, Iyad

"…For comparative purposes, the same linked-based neighbourhood selection strategy is utilized with other three optimization algorithms, including particle swarm optimization, salp swarm optimization, and wind-driven algorithm. …"
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Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System حسب Alaa Altawallbeh (22565837)

"…We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …"

Enhancing multilayer perceptron neural network using archive-based harris hawks optimizer to predict gold prices حسب Abu Doush, Iyad

"…The performance of the proposed AHHO-NN model is compared against four swarm intelligence algorithms (i.e., HHO-NN, JAYA-NN, MFO-NN, PSO-NN) as well as four classical machine learning techniques (i.e., linear regression (LR), MLP Regressor (MLP), RANSAC Regressor (RANSAC), and TheilSen Regressor (TR)). …"
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Improving multilayer perceptron neural network using two enhanced moth-flame optimizers to forecast iron ore prices حسب Ahmed, Basem

"…We compare our two proposed MFO algorithms, the roulette wheel moth-flame optimization algorithm and the global best moth-flame optimization algorithm, against four swarm intelligence algorithms and five classical machine learning techniques when predicting the iron ore price. …"
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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. …"

Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO حسب Majedeh Gheytanzadeh (17541927)

"…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …"

The survey of cluster based data collection process for iot enabled wireless sensor network using several optimization technique حسب Abirami, R.

"…The study analyses nature-based metaheuristic methods such as the Genetic Algorithms, Particle Swarm Optimization, Firefly Optimization, Gray Wolf Optimization and Water-Cycle Algorithms, and specialised protocols of clustering, routing and data aggregation. …"
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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

"…CEC2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO algorithm. For the vehicle cruise control system, we confirm the more excellent performance of the proposed method against particle swarm, gray wolf, salp swarm, and original Aquila optimizers using statistical, Wilcoxon signed-rank, time response, robustness, and disturbance rejection analyses. …"
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Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem حسب Denis Alicic (23073484)

"…The need for effective solution methods arises from the problem’s large-scale complexity and the strong influence of spatial and capacity constraints on solution quality. We propose a twofold contribution: first, an adaptive greedy algorithm that generates high-quality initial solutions, achieving markedly better results than traditional constructive heuristics at comparable computational costs; and second, the adaptation of the Matheuristic Fixed Set Search (MFSS) to the TSCFLP. …"

Enhanced Control of Single-Stage PV-STATCOM Using Hybrid MPPT and Adaptive AHLMS for Power Quality Improvement حسب Nagwa F. Ibrahim (17334201)

"…It employs a hybrid pelican and perturbs and observe and particle swarm optimization (PSO) based maximum power point tracking (MPPT) algorithm to consistently extract peak power from the PV array. …"

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

"…The formulation is decomposed into two interdependent sub-problems and solved using a combination of metaheuristic and deterministic optimization techniques. A sample case study is presented to illustrate the performance of the algorithm.…"
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DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications حسب Danya A. Saifaldeen (19498705)

"…The aim is to enhance the secrecy capacity (SC) of the system by optimizing the beamforming weights at the VLC fixtures, the beamforming weights at the mmWave AP, the mirror array configurations, and the phase shift vector while meeting specific power constraints. …"

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). …"
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Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring حسب Zina Chkirbene (16869987)

"…By formulating the video resource allocation challenge as a multi-objective optimization problem, the framework aims to minimize network delays while respecting node capacity limitations. …"

Joint Beamforming Design and Power Minimization for Friendly Jamming Relaying Hybrid RF/VLC Systems حسب Jaber Al-Khori (16855470)

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas حسب Marwan Dhuheir (19170898)

"…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …"