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  1. 521

    Multi-Timescale Nested Hydropower Station Optimization Scheduling Based on the Migrating Particle Whale Optimization Algorithm by Mi Zhang, Guosheng Zhou, Bei Liu, Dajun Huang, Hao Yu, Li Mo

    Published 2025-04-01
    “…To address these limitations, this paper proposes the Migrating Particle Whale Optimization Algorithm (MPWOA), which initializes the population using chaotic mapping, incorporates a particle swarm mechanism to enhance exploitation during the spiral predation phase, and integrates the black-winged kite migration mechanism to improve stochastic search performance. …”
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    Article
  2. 522
  3. 523

    Optimized solar PV integration for voltage enhancement and loss reduction in the Kombolcha distribution system using hybrid grey wolf-particle swarm optimization by Awot Getachew Abera, Tefera Terefe Yetayew, Assen Beshr Alyu

    Published 2025-06-01
    “…A hybrid optimization approach combining Particle Swarm Optimization and Grey Wolf Optimization algorithms is proposed for determining optimal sizing and placement of PV-based DGs. …”
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    Article
  4. 524

    Cable Force Optimization of Circular Ring Pylon Cable-Stayed Bridges Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization by Shengdong Liu, Fei Chen, Qingfu Li, Xiyu Ma

    Published 2025-07-01
    “…This study proposes a hybrid approach combining Response Surface Methodology (RSM) and Multi-Objective Particle Swarm Optimization (MOPSO) to overcome these challenges. …”
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    Article
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    Application research on classification and integration model of innovation and entrepreneurship education resources based on GNN-PSO algorithm by Yongjian Dong

    Published 2025-12-01
    “…Therefore, this study proposes a classification and integration model of innovation and entrepreneurship education resources based on GNN-PSO (graph neural networks and particle swarm optimization). The model uses the powerful feature extraction ability of GNN to dig deep into the internal relationship between educational resources. …”
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    Article
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    Sleep scheduling-aware minimum power broadcast in wireless ad hoc networks based on discrete particle swarm optimization by Xiao-jian ZHU, Jun SHEN

    Published 2013-06-01
    “…For the minimum power broadcast scheduling problem where network uses sleep scheduling and each node's transmission power is continuously adjustable,a recursive approach to compute the optimal transmission scheduling of a node was firstly presented,and then a discrete particle swarm optimization algorithm to construct the minimum power broadcast scheduling was proposed.This algorithm searches for the optimal broadcast arborescence,and utilizes the greedy algorithm based on the minimization of the broadcast's power increment and the local optimization algorithm based on the heuristic adjustment of the broadcast arborescence to improve the convergence speed and the result quality.The simulation results show that the proposed algorithm is able to effectively reduce the broadcast power.…”
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    Article
  11. 531

    Indoor High Precision Three-Dimensional Positioning System Based on Visible Light Communication Using Particle Swarm Optimization by Ye Cai, Weipeng Guan, Yuxiang Wu, Canyu Xie, Yirong Chen, Liangtao Fang

    Published 2017-01-01
    “…To solve these problems, a novel VLC positioning system based on modified particle swarm optimization (PSO) algorithm is put forward in this article. …”
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    Article
  12. 532

    A spherical vector-based adaptive evolutionary particle swarm optimization for UAV path planning under threat conditions by Yanfei Liu, Hao Zhang, Hao Zheng, Qi Li, Qi Tian

    Published 2025-01-01
    “…However, existing particle swarm optimization (PSO) algorithms struggle with these problems as they fail to consider UAV dynamics, resulting in many infeasible solutions and poor convergence to optimal solutions. …”
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    Article
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  15. 535

    Control parameter identification method for virtual synchronous generator considering electric vehicles based on dynamic particle swarm optimization by Dongqi Wu, Yong Hu

    Published 2025-04-01
    “…To address the issues of insufficient control parameter identification accuracy and convergence speed during the grid connection of distributed power sources, a control parameter identification method for the Virtual Synchronous Generator (VSG) converter model considering the integration of electric vehicles (EVs) based on the dynamic particle swarm optimization algorithm is proposed. …”
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    Article
  16. 536

    Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

    Published 2024-12-01
    “…In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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    Article
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    Optimum Allocation of Microgrid and D-STATCOM in Radial Distribution System for Voltage Profile Enhancement Using Particle Swarm Optimization by Mezigebu Getinet Yenealem

    Published 2024-01-01
    “…Particle swarm optimization (PSO), a powerful and efficient metaheuristic algorithm, is utilized to determine the optimal sizing of MG and D-STATCOM controllers. …”
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    Article
  19. 539

    Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier by C. V. Subbulakshmi, S. N. Deepa

    Published 2015-01-01
    “…This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. …”
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  20. 540

    Clustering analysis of Yue opera character tone trends based on quantum particle swarm optimization for fuzzy C-means. by Yuhang Zhang, Xiaofeng Wu, Jiawei Xu, Zihao Ning, Xiao Han

    Published 2025-01-01
    “…We introduce a fuzzy C-means clustering method enhanced by quantum particle swarm optimization (QPSO) to manage data uncertainties, improving classification accuracy and convergence speed. …”
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    Article