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3301
Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts
Published 2025-01-01“…In addition, the existing NC process decision methods, such as the genetic algorithm, ant colony algorithm, and particle swarm algorithm, have not been combined with the reuse approach. …”
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3302
Applied AMT machine learning and multi-objective optimization for enhanced performance and reduced environmental impact of sunflower oil biodiesel in compression ignition engine
Published 2024-11-01“…Subsequently, this study explores the application of an alternating model tree (AMT) machine learning algorithm to establish relationships between independent factors, specifically torque and biodiesel volume (%vol), and dependent variables, including BTE, BSFC, CO, and NOx in a combustion engine. …”
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3303
A prior information-based multi-population multi-objective optimization for estimating 18F-FDG PET/CT pharmacokinetics of hepatocellular carcinoma
Published 2025-02-01“…The single-individual Levenberg–Marquardt (LM) algorithm, single-population algorithms (Particle Swarm Optimization (PSO), Differential Evolution (DE), and Genetic Algorithm (GA)) and p-MPMO optimization algorithms (p-MPMOPSO, p-MPMODE, and p-MPMOGA) were used to estimate the parameters. …”
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3304
Multiobjective optimization of CO2 injection under geomechanical risk in high water cut oil reservoirs using artificial intelligence approaches
Published 2025-07-01“…Therefore, a hybrid optimization framework was designed that combines artificial intelligence methods (Support Vector Regression with the Gaussian kernel, Gaussian-SVR or Long Short-Term Memory, LSTM) and multi-objective optimization algorithms (multiple objective particle swarm optimization, MOPSO or Non-dominated Sorting Genetic Algorithm II, NSGA-II) to find the optimal CO2 injection and production strategies under different water cut. …”
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3305
Adaptive Path Planning for Multi-UAV Systems in Dynamic 3D Environments: A Multi-Objective Framework
Published 2024-12-01“…Its angular deviation of 8.0° ensures smoother trajectories than traditional methods like Genetic Algorithm and Particle Swarm Optimization (PSO). Moreover, AMOPP achieves a 0% collision rate across all simulations, surpassing heuristic-based methods like Cuckoo Search and Bee Colony Optimization, which exhibit higher collision rates. …”
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3306
Small Modular Reactor based on NuScale with Thorium base
Published 2025-07-01“…To meet substantial computational demands, they ran these simulations on the Lobo Carneiro supercomputer at NACAD/UFRJ. The team applied a Particle Swarm Optimization (PSO) algorithm to find the best seed-to-blanket volume ratio, thereby maximizing U-233 production and achieving a self-sustaining fuel cycle. …”
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3307
Enhancing renewable energy integration through strategic stochastic optimization planning of distributed energy resources (Wind/PV/SBESS/MBESS) in distribution systems
Published 2025-05-01“…A hybrid optimization approach combining the non-dominated sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO) with a decision-making algorithm is proposed to solve the planning problem. …”
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3308
Spatial Characteristics and Influence of Topography and Synoptic Systems on PM2.5 in the Eastern Monsoon Region of China
Published 2023-06-01“…The spatial distribution and interregional influence of fine particle pollution under different synoptic weather and topography in the eastern monsoon region of China were illustrated. …”
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3309
Investigation on the Role of Artificial Intelligence in Measurement System
Published 2025-01-01“…Hardware approach with soft computation has reduced non linearity error by 84.63% for thermocouple linearization, meanwhile novel hybrid approach using genetic algorithm (GA) and particle swarm optimization (PSO) combined with back propagation neural network (BPNN) have reduced mean absolute percentage error to 1.2 % for industrial weir than conventional hardware approaches using sensors and signal conditioning circuits but at higher computational cost. …”
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3310
Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment
Published 2025-07-01“…This research aims to optimize power usage by reducing peak loads and electricity costs through the integration of RESs, such as solar or photovoltaic (PV) systems, while considering grid limitations, PV capacity, appliance ON/OFF schedules, and time-of-use tariffs. A genetic algorithm (GA) based optimization technique was employed to evaluate the performance of a HEMS and validated with particle swarm optimization (PSO) technique under identical initial conditions for each appliance and their corresponding energy pricing over different periods. …”
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3311
Variation Characteristics of Mass-Loss Rate in Dynamic Seepage System of the Broken Rocks
Published 2018-01-01“…When the collapse column and its adjacent rocks in complex geological structures are disturbed by mining, concomitant fine particle migration, mass loss, and porous structure variation during the water seepage process in broken rocks are the inherent causes for collapse column activation and water inrush. …”
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3312
Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition
Published 2024-11-01“…The results demonstrate that the proposed algorithm effectively mitigates the impact of scattering from aerosols and other particles, reducing the heading angle error to within 2° under sunny, cloudy, overcast and sandy conditions.…”
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3313
Multi-Modal Federated Learning Over Cell-Free Massive MIMO Systems for Activity Recognition
Published 2025-01-01“…Additionally, we employ a modified Particle Swarm Optimization (PSO) algorithm for efficient resource allocation. …”
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3314
Wavenumber-Domain Joint Estimation of Rotation Parameters and Scene Center Offset for Large-Angle ISAR Cross-Range Scaling
Published 2025-05-01“…Utilizing this model and the sensitivity of wavenumber-domain imaging to SCO, a joint estimation algorithm that combines particle swarm optimization (PSO) and image entropy evaluation is proposed, achieving accurate parameter estimation. …”
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3315
Blockchain-based heterogeneous resource configuration scheme in computing power network
Published 2025-07-01“…Given the complexity of the original problem, we decompose it into two subproblems and solve each using the Lagrange multiplier iterative algorithm. To validate the effectiveness of our proposed solution, we compare it with several baseline approaches, including those based on Particle Swarm Optimization (PSO) and reinforcement learning methods such as Proximal Policy Optimization (PPO). …”
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3316
Metaheuristic Optimization of Fractional Order Incremental Conductance (FO-INC) Maximum Power Point Tracking (MPPT)
Published 2019-01-01“…Due to its simplicity and efficiency, the incremental conductance MPPT (INC-MPPT) is one of the most popular algorithms used in the PV scheme. However, owing to the nonlinearity and fractional order (FO) nature of both PV and DC-DC converters, the conventional INC algorithm provides a trade-off between monitoring velocity and tracking precision. …”
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3317
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
Published 2021-06-01“…The two sets of selected features are based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) approach respectively. …”
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3318
Machine learning-based multiphysics model for corrosion fatigue crack propagation in aluminum alloy
Published 2025-05-01“…In view of the complexity and nonlinearity of model parameter optimization, a particle swarm optimization algorithm was utilized to mutually feedback experimental measurement results with simulation results, optimizing the unknown parameters in the model to obtain a high-fidelity corrosion fatigue model. …”
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3319
A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance
Published 2020-01-01“…The second objective is the acceptable walking distance from the parking space to the destination. The particle swarm optimization (PSO) algorithm is used to solve this model. …”
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3320
Multi-Objective Optimization for Volt-Var Parameter Tuning: Reducing Losses and Voltage Unbalance in Distribution Systems
Published 2025-01-01“…The optimization problem is solved using NSGA-II (Non-dominated Sorting Genetic Algorithm II) and MOPSO (Multi-Objective Particle Swarm Optimization), with three-phase power flow analysis performed using OpenDSS integrated into a Python-based framework. …”
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