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1381
Optimizing intelligent reflecting surface assisted visible light communication networks under blockage and practical constraints using TLBO for IoT applications
Published 2025-07-01“…Additionally, detailed convergence analysis demonstrates that TLBO performs better than Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in terms of convergence speed, higher fitness value and lower sensitivity to initial conditions, making it most suitable for real-time IRS-VLC based IoT applications.…”
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1382
Enhancing Hajj and Umrah Services Through Predictive Social Media Classification
Published 2025-01-01“…The primary objective of this system is to efficiently classify and analyze social media content related to Hajj and Umrah services. To improve the effectiveness of this classification model, we introduce a predictive optimization strategy that employs a deep neural network as the learning module and utilizes particle swarm optimization to refine the weighting parameters. …”
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1383
Optimizing the core loading pattern and fuel composition in a hexagonal small modular nuclear reactor via ANN-PSO approach
Published 2025-06-01“…The gadolinia concentration was effectively optimized using the Particle Swarm Optimization (PSO) algorithm. The best model, based on TCs and PPFs, was selected. …”
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1384
Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage
Published 2025-06-01“…Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. …”
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1385
Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome
Published 2025-05-01“…Hyperparameters for each model were optimized using the particle swarm optimization (PSO) algorithm on the validation set. …”
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1386
A stochastic optimization method for economic microgrid operation based on "source-load operation" mode classification
Published 2025-06-01“…Finally, the adaptive weighted particle swarm optimization (AW-PSO) is employed to solve the stochastic optimization model for microgrid operations. …”
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1387
Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM
Published 2025-01-01“…The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. …”
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1388
Coordinated Optimization and Operational Strategy for Multi-type Energy Storage in Regional Integrated Energy Systems
Published 2024-09-01“…And then, by taking into account three objectives of economy, environment, and energy efficiency, the model was used to optimize the operational parameters of systems by utilizing the improved multi-objective particle swarm optimization (MOPSO) algorithm in conjunction with the TOPSIS method. …”
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1389
Collaborative Planning for Distribution Network and PV-ESS in the Marketization Environment
Published 2022-01-01“…In addition, the timing operation results of the distribution network in typical scenes were obtained in the operation layer using the benefit coupling model and energy storage operation strategy. The double-layer improved particle swarm optimization algorithm was applied to run the model. …”
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1390
Cascade Control of Grid-Connected PV Systems Using TLBO-Based Fractional-Order PID
Published 2019-01-01“…The superiority of the proposed TLBO-based FOPID controller has been demonstrated by comparing the results with recently published optimization techniques such as genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). …”
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1391
Presenting a Fuzzy Multiobjective Mathematical Model of the Reverse Logistics Supply Chain Network in the Automotive Industry to Reduce Time and Energy
Published 2023-01-01“…Deterministic methods, genetic algorithm, particle swarm algorithm, and several scenarios with different aspects have been used to solve the model. …”
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1392
Visual Classification of Music Style Transfer Based on PSO-BP Rating Prediction Model
Published 2021-01-01“…At the same time, we take advantage of the BP neural network’s ability to handle complex nonlinear problems and construct a rating prediction model between the user and item attribute features, referred to as the PSO-BP rating prediction model, by combining the features of global optimization of particle swarm optimization algorithm, and make further improvements based on the traditional collaborative filtering algorithm.…”
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1393
Design, Modeling, and Optimization of a Nearly Constant Displacement Reducer with Completely Distributed Compliance
Published 2025-03-01“…On the basis of sensitivity analysis to structure parameters, including node positions and beam parameters, the Particle Swarm Optimization (PSO) algorithm is used to optimize the displacement reduction performance. …”
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1394
Machine learning prediction and explainability analysis of high strength glass powder concrete using SHAP PDP and ICE
Published 2025-07-01“…To further enhance performance, XGB was optimized using Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO). …”
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1395
Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders.
Published 2025-01-01“…Additionally, the model's findings indicate that the proposed PO version performs comparably to the Differential Evolution (DE), Particle Swarm Optimization (PSO), and Satin bowerbird optimizer (SBO) algorithms.…”
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1396
Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite
Published 2024-12-01“…Using S-G smoothing filtering (S-G), multivariate scattering correction (MSC), standard normal transformation (SNV), second derivative (SD), reciprocal logarithm (LR) and continuum removal (CR) to preprocess the data, the spectral characteristics and their correlation with water content were analyzed. In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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1397
State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models
Published 2025-06-01“…These include the barnacle mating optimizer-deep neural networks (BMO-DNNs) with an MAE of 5.3848, an RMSE of 7.0395, and a convergence value of 0.0492; the evolutionary mating algorithm-deep neural networks (EMA-DNNs) with an MAE of 7.6127, an RMSE of 11.2287, and a convergence value of 0.0536; and the particle swarm optimization-deep neural networks (PSO-DNNs) with an MAE of 4.3089, an RMSE of 5.9672, and a convergence value of 0.0345. …”
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1398
An Optimization Method for Indoor Pseudolites Anchor Layout Based on MG-MOPSO
Published 2025-05-01“…To address the challenge of optimizing the layout of pseudolite anchor points in complex indoor environments with significant occlusions, this paper proposes a multi-objective particle swarm optimization algorithm (MG-MOPSO). The algorithm leverages a minimum geometric dilution of precision (GDOP) configuration to optimize anchor deployment, aiming to meet the high-precision requirements of indoor pseudolite positioning systems. …”
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1399
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Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators
Published 2025-08-01“…The model incorporates temperature variations that affect the PV output, energy storage capacity, conversion efficiency, and EV charging demand, all of which improve numerical accuracy. A new pricing algorithm based on peak-valley differences is proposed that considers the impact of EV penetration and temperature fluctuations. …”
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