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  1. 241

    A Hybrid Optimization Algorithm for the Synthesis of Sparse Array Pattern Diagrams by Youzhi Liu, Linshu Huang, Xu Xie, Huijuan Ye

    Published 2025-06-01
    “…To comprehensively address the challenges of aperture design, element spacing optimization, and sidelobe suppression in sparse radar array antennas, this paper proposes a hybrid particle swarm optimization (PSO) algorithm that integrates quantum-behavior mechanisms with genetic mutation. …”
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    Article
  2. 242

    An efficient hybrid algorithm based on particle swarm optimisation and teaching‐learning‐based optimisation for parameter estimation of photovoltaic models by Dianlang Wang, Zhongrui Qiu, Qi Yin, Haifeng Wang, Jing Chen, Chengbi Zeng

    Published 2024-12-01
    “…In order to estimate the unknown parameters of the PV models more precisely and reliably, an efficient hybrid algorithm based on particle swarm optimisation and teaching‐learning‐based optimisation (PSOTLBO) is proposed in this paper. …”
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    Article
  3. 243

    Optimization of Ship Permanent Magnet Synchronous Motor ADRC Based on Improved QPSO by Hongbo Xu, Jundong Zhang, Jiale Liu, Yang Cao, Ao Ma

    Published 2025-02-01
    “…To address the impact of load variations, external environmental changes, and the tuning of the parameters on Permanent Magnet Synchronous Motors (PMSMs) used in ships, this study proposes an Active Disturbance Rejection Control (ADRC) strategy for PMSMs, optimized by the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm. First, based on the PMSM model, the study addresses the limited disturbance rejection capability of the traditional fal function in the Extended State Observer (ESO) of conventional ADRC. …”
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    Article
  4. 244

    A Novel Multi-Objective Trajectory Planning Method for Robots Based on the Multi-Objective Particle Swarm Optimization Algorithm by Jiahui Wang, Yongbo Zhang, Shihao Zhu, Junling Wang

    Published 2024-11-01
    “…Secondly, the joint space trajectory of the robot is constructed with fifth-order B-spline functions, realizing the continuous position, velocity, acceleration, and jerk of each joint. Then, the improved multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the trajectory, and the distribution uniformity, convergence, and diversity of the obtained Pareto front are good. …”
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    Article
  5. 245

    Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

    Published 2023-01-01
    “…Finally, by introducing the Particle Swarm Optimization (PSO) algorithm into the optimization of the initial weights and thresholds of the BP neural network, the BP neural network is improved based on the momentum factor and adaptive learning rate, and the high detection rate and low false detection rate are realized. …”
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    Article
  6. 246

    The Optimal Location of Interline Power Flow Controller in the Transmission Lines for Reduction Losses using the Particle Swarm Optimization Algorithm by Mehrdad Ahmadi Kamarposhti

    Published 2024-02-01
    “…This paper proposed, the optimal location of the IPFC in electrical power systems, using the particle swarm optimization algorithm. Expression of sample figure and analysis of the sample system shows that IPFC is effective to minimize the power losses in the power system.…”
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    Article
  7. 247

    Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

    Published 2025-07-01
    “…This research presents a Particle Swarm Optimization (PSO) algorithm to optimize the deployment of electronic information sensing nodes. …”
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    Article
  8. 248

    On the optimal control of single-stage hybrid manufacturing systems via novel and different variants of particle swarm optimization algorithm by M. Senthil Arumugam, M. V. C. Rao

    Published 2005-01-01
    “…This paper presents several novel approaches of particle swarm optimization (PSO) algorithm with new particle velocity equations and three variants of inertia weight to solve the optimal control problem of a class of hybrid systems, which are motivated by the structure of manufacturing environments that integrate process and optimal control. …”
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    Article
  9. 249

    Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

    Published 2025-12-01
    “…In addition, it examines 2,000 random surface soil samples, ranging from 0 to 20 cm, that were optimized using genetic algorithms (GA), particle swarm optimization (PSO), and Optuna. …”
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    Article
  10. 250
  11. 251

    Study of the ternary correlation quantum-behaved PSO algorithm by Tao WU, Xi CHEN, Yu-song YAN

    Published 2015-03-01
    “…In order to more effectively utilize existing information and improve QPSO's (quantum-behaved particle swarm optimization) convergence performance, the ternary correlation QPSO (TC-QPSO) algorithm was proposed based on the analysis of the random factors in location formula. …”
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    Article
  12. 252

    Study of the ternary correlation quantum-behaved PSO algorithm by Tao WU, Xi CHEN, Yu-song YAN

    Published 2015-03-01
    “…In order to more effectively utilize existing information and improve QPSO's (quantum-behaved particle swarm optimization) convergence performance, the ternary correlation QPSO (TC-QPSO) algorithm was proposed based on the analysis of the random factors in location formula. …”
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    Article
  13. 253
  14. 254

    Power Loss Reduction and Reliability Improvement of Radial Distribution Systems Using Optimal Capacitor Placement Technique by Mohanad Muneer Yaqoob, Ali Nasser Hussain, Wathiq Rafa Abed, Daniel Augusto Pereira

    Published 2024-03-01
    “…The proposed technique has been tested with 69 typical IEEE RDS buses using the Improved Binary Particle Swarm Optimization (IBPSO) algorithm. …”
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    Article
  15. 255

    A novel particle swarm optimisation with mutation breeding by Zhe Liu, Fei Han, Qing-Hua Ling

    Published 2020-10-01
    “…The diversity of the population is a key factor for particle swarm optimisation (PSO) when dealing with most optimisation problems. …”
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    Article
  16. 256

    Situation Awareness and Tracking Algorithm for Countering Low-Altitude Swarm Target Threats by Nannan Zhu, Fuli Zhong, Xueyue Lei, Guo Niu, Hongtu Xie, Yue Zhang

    Published 2025-03-01
    “…Algorithmically, the random matrix model is enhanced by introducing extension parameters to accurately capture the dynamic changes in swarm shape. …”
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    Article
  17. 257
  18. 258

    Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines by Lelisa Wogi, Amruth Thelkar, Tesfabirhan Shoga Tahiro, Tadele Ayana, Shabana Urooj, Samia Larguech

    Published 2022-04-01
    “…This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
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    Article
  19. 259

    Improving energy efficiency for intelligent reflecting surface assisted PD-NOMA in EH relaying network by Hong Nguyen-Thi, Thuc Kieu-Xuan, Thang Le-Nhat, Anh Le-Thi

    Published 2025-02-01
    “…We also construct a Particle swarm optimization (PSO)-based program to optimize the EE depending on power allocation for NOMA users and phase shift of the IRS elements. …”
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  20. 260

    FATIGUE CRACK GROWTH PREDICTION BASED ON IPSO-PF ALGORITHM by JIN Ting, WANG Xiaolei, LIU Yu, YUAN Jianming

    Published 2025-04-01
    “…The traditional Paris formula ignores the influence of various uncertain factors in the crack growth process, which leads to a big difference between the predicted crack growth process and the real crack growth process. In order to improve the prediction accuracy of fatigue crack growth, a fatigue crack growth prediction method based on the improved particle swarm optimization particle filtering (IPSO-PF) algorithm was proposed. …”
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    Article