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1181
Sustainable closed-loop supply chain network planning considering price competition using particle chaotic ant colony algorithm
Published 2025-05-01“…Thirdly, the problems of premature convergence and slow convergence during the traditional particle swarm optimization algorithm and genetic algorithm are solved with the particle chaotic ant colony algorithm (PSCACO). …”
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1182
Research on Capacitated Multi-Ship Replenishment Path Planning Problem Based on the Synergistic Hybrid Optimization Algorithm
Published 2025-05-01“…To evaluate performance, the SHOA is benchmarked against ACO, the GA, the particle swarm optimization algorithm, and the simulated annealing algorithm for the capacitated vehicle routing problem. …”
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1183
A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici...
Published 2024-09-01“…Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. The simulation results show that the proposed scheduling strategy has a lower charging cost (CNY 11,032.4) and lower load mean square error (12.84 × 10<sup>5</sup> kW<sup>2</sup>) than the strategy employed in the comparison experiment, which ensures the economic and stable operation of the microgrid.…”
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1184
Design of Cloud-Based Complex VR 3D Scene Interaction Based on Attribute Preferences
Published 2025-01-01“…The study leverages Reinforcement Learning (RL) and Particle Swarm Optimization (PSO) to address critical challenges such as user interface adaptability and cloud resource allocation. …”
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1185
An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions
Published 2025-09-01“…A comprehensive study compares the HHO technique with established methods such as perturb and observe (P&O), modified P&O (MP&O), incremental conductance (IC), Spline MPPT, particle swarm optimization (PSO), grasshopper optimization (GHO), and grey wolf optimization (GWO) across fast-changing irradiance, partial shading, complex partial shading, and load-changing conditions. …”
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1186
Optimizing Deep Learning Models with Improved BWO for TEC Prediction
Published 2024-09-01Get full text
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1187
Progress in Construction Robot Path-Planning Algorithms: Review
Published 2025-01-01Get full text
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1188
A systematic review on search‐based test suite reduction: State‐of‐the‐art, taxonomy, and future directions
Published 2023-04-01Get full text
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1189
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1190
Hybrid precoding method for millimeter-wave massive MIMO systems based on IAFS algorithm
Published 2021-08-01Get full text
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1191
Ship Formation and Route Optimization Design Based on Improved PSO and D-P Algorithm
Published 2025-01-01“…Based on this, a ship formation model combining improved particle swarm optimization algorithm and a generative route optimization method based on improved Douglas-Peucker algorithm are proposed. …”
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1192
VMD‐FBCCA classification method for SSVEP brain–computer interfaces
Published 2025-03-01“…Next, a particle swarm algorithm is employed to optimize the weights of the IMFs and reconstruct the EEG signals. …”
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1193
An analysis of unconventional grid sizes for wind farm layout optimization using a genetic algorithm
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1194
Time-optimal trajectory planning for excavators operating arm based on SA-PSO algorithm
Published 2025-01-01“…ObjectiveIn view of the problems of unstable operation, low optimization efficiency and falling into local optimum when optimizing the operation trajectory with a single intelligent algorithm, this paper proposes to combine simulated annealing and particle swarm optimization (SA-PSO) to perform optimal time planning for the excavation task trajectory of the excavator operating arm.MethodsFirstly, in the D-H coordinate system, the mechanism diagram of the excavator operating arm is constructed to establish its kinematic model; secondly, the 4-3-3-3-4 piecewise polynomial is used for interpolation, and the SA-PSO algorithm is used to optimize the high-efficiency excavation task trajectory under the constraints of joint velocity and acceleration; finally, under the same operation task, the differential evolution algorithm (DE) and particle swarm optimization algorithm (PSO) are used in turn to obtain the time optimal trajectory.ResultsThe experimental results show that the optimal time trajectory obtained by the hybrid algorithm has shorter operation efficiency and the smallest impact, which can effectively reduce the wear of each joint hydraulic cylinder. …”
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1195
APPLICATION OF SEMI SUPERVISED LAPLACE SCORE IN ROLLING BEARING FAULT DIAGNOSIS (MT)
Published 2023-01-01“…SSLS applies the semi supervised idea to the Laplace score feature selection method, uses a small number of labeled samples and a large number of unlabeled samples, and combines KPCA to excavate fault features for a second time. At the same time, particle swarm optimization-based support vector machine(PSO-SVM) algorithm is used for fault classification. …”
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1196
Determined the Edges Using the ant Colony Algorithm and Apply them to Medical Images
Published 2012-12-01Get full text
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1197
Day-Ahead Scheduling for Economic Dispatch of Combined Heat and Power With Uncertain Demand Response
Published 2022-01-01“…The above problem is solved through the use of the co-evolutionary particle swarm optimization (C-PSO) algorithm and the proposed model is implemented on a standard seven-unit system for a period of 24 hours.…”
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1198
Reducing PAPR in NOMA Waveforms Using Genetic-Enhanced PTS and SLM: A Low-Complexity Approach for Improved throughput, power spectral density, and Power Efficiency
Published 2025-06-01“…To overcome these issues, this paper introduces new Particle Swarm Optimization (PSO)-improved partial transmit sequence (PTS) and Selective Mapping (SLM) schemes that optimally choose phase factors with much lower search complexity. …”
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1199
A hybrid deep learning and differential evolution approach for accurate fake news detection
Published 2025-12-01“…Experimental results on benchmark datasets demonstrate that the hybrid approach achieves superior accuracy, precision, recall, and F1-score compared to existing methods such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and standalone deep learning models. …”
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1200
Robust Framework for PMU Placement and Voltage Estimation of Power Distribution Network
Published 2025-01-01“…The suggested method uses a hybrid Multi-Objective Particle Swarm Optimization and Differential Evolution (MOPSO-DE) algorithm to find the best PMU positions and the Weighted Least Squares (WLS) method to estimate voltage magnitude. …”
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