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  1. 541

    Improving Portfolio Management Using Clustering and Particle Swarm Optimisation by Vivek Bulani, Marija Bezbradica, Martin Crane

    Published 2025-05-01
    “…Particularly, this research examines different approaches for handling missing values and volatility, while examining their effects on optimal portfolios. For this portfolio optimisation task, this study employs a metaheuristic approach through the Swarm Intelligence algorithm, particularly Particle Swarm Optimisation and its variants. …”
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    Article
  2. 542

    KPLS Optimization With Nature-Inspired Metaheuristic Algorithms by Jorge Daniel Mello-Roman, Adolfo Hernandez

    Published 2020-01-01
    “…It was solved using nature-inspired metaheuristic algorithms: the genetic algorithm, particle swarm optimization, grey wolf optimization and the firefly algorithm. …”
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    Article
  3. 543

    A Particle Swarm Optimization Approach to Solve the Vehicle Routing Problem with Cross-Docking and Carbon Emissions Reduction in Logistics Management by Shih-Che Lo

    Published 2022-09-01
    “…<i>Methods</i>: A heuristic approach based on Particle Swarm Optimization, called ePSO, was proposed and implemented in this paper to solve the vehicle routing problems with cross-docking and carbon emissions reduction at the same time. …”
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    Article
  4. 544

    A Novel Chaotic Particle Swarm Optimized Backpropagation Neural Network PID Controller for Four-Switch Buck–Boost Converters by Luoyao Ren, Dazhi Wang, Xin Yan, Yupeng Zhang, Jiaxing Wang

    Published 2024-11-01
    “…To address these challenges, chaotic optimization algorithms are integrated with BPNN. The chaotic particle swarm optimization (CPSO) algorithm enhances the global search capability, enabling a faster system response and minimizing overvoltage. …”
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    Article
  5. 545

    Electric Vehicle Charging Load Forecasting Method Based on Improved Long Short-Term Memory Model with Particle Swarm Optimization by Xiaomeng Yang, Lidong Zhang, Xiangyun Han

    Published 2025-03-01
    “…In this context, the present study proposes a Particle Swarm Optimization (PSO)-enhanced Long Short-Term Memory (LSTM) network forecasting model. …”
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    Article
  6. 546

    Energy Management of a Semi-Autonomous Truck Using a Blended Multiple Model Controller Based on Particle Swarm Optimization by Mohammad Ghazali, Ishaan Gupta, Kemal Buyukkabasakal, Mohamed Amine Ben Abdallah, Caner Harman, Berfin Kahraman, Ahu Ece Hartavi

    Published 2025-05-01
    “…The approach combines a particle swarm optimization algorithm to determine optimal controller gains and a multiple model controller to adapt these gains dynamically based on real-time vehicle mass. …”
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    Article
  7. 547
  8. 548

    A hybrid machine learning method of support vector regression with particle swarm optimization for predicting IRI in continuously reinforced concrete pavement by Ali Alnaqbi, Waleed Zeiada, Ghazi Al-Khateeb

    Published 2025-08-01
    “…In order to forecast IRI using data taken from the Long-Term Pavement Performance (LTPP) database, this study proposes a hybrid machine learning model that combines Support Vector Regression (SVR) and Particle Swarm Optimization (PSO). Incorporating structural, climatic, and traffic-related variables, 395 observations from 33 CRCP sections were used. …”
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    Article
  9. 549

    High-speed threat detection in 5G SDN with particle swarm optimizer integrated GRU-driven generative adversarial network by R. Shameli, Sujatha Rajkumar

    Published 2025-03-01
    “…The DL model integrates the Particle Swarm Optimizer-Gated Recurrent Unit Layer-Generative Adversarial Network-Intrusion Detection System classifier (PSO-GRUGAN-IDS). …”
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    Article
  10. 550
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  12. 552

    Classification algorithm for imbalance data of ECG based on PSOFS and TSK fuzzy system by Xinhui LI, Qing SHEN, Xiongtao ZHANG

    Published 2022-09-01
    “…A new classification model of electrocardiogram (ECG) signal based on particle swarm optimization feature selection (PSOFS) and TSK (Takagi-Sugeno-Kang) fuzzy system was proposed, i.e., parallel ensemble fuzzy neural network based on PSOFS and TSK (PE-PT-FN), which was used for ECG prediction.Each class sample in the training set was randomly sampled, and the samples obtained by randomly sampled were added.Then, the feature selection method PSOFS was carried out independently and parallelly.In PSOFS, particles that were random initial positions represent different feature subsets and converge to the optimal positions after many iterations.Each subset had a corresponding feature subset.Several groups of TSK fuzzy neural network (TSK-FNN) were trained by each feature subset in parallel.Medical researchers could effectively find the correlation between ECG signal data and different types of disease through the interpretability of the fuzzy system and the feature subsets by the PSOFS algorithm.Experiments prove that PE-PT-FN greatly improves the macro-R to 92.35% while retaining interpretability.…”
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  13. 553

    A Thorough Comparative Analysis of PI and Sliding Mode Controllers in Permanent Magnet Synchronous Motor Drive Based on Optimization Algorithms by Fatemeh Khorsand, Reza Shahnazi, Esmael Fallah

    Published 2019-12-01
    “…Thus, based on this cost function a nonlinear optimization problem is defined. To solve the optimization problem and consequently derive the optimal values for the parameters of the controllers, particle swarm optimization (PSO) and grey wolf optimization (GWO) algorithms are employed. …”
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    Article
  14. 554
  15. 555

    Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

    Published 2025-10-01
    “…This research utilizes swarm intelligence algorithmsParticle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
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    Article
  16. 556

    An energy-efficient routing protocol for wireless body area networks using hybrid artificial bee colony optimization and chicken swarm optimization algorithm by A. Dinesh, J. Rangaraj

    Published 2025-04-01
    “…The proposed work simulates a variety of scenarios to show the suggested algorithm’s superiority over Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), ABC, and Grey Wolf Optimization (GWO) protocols. …”
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    Article
  17. 557
  18. 558

    Grey Wolf Optimization- and Particle Swarm Optimization-Based PD/I Controllers and DC/DC Buck Converters Designed for PEM Fuel Cell-Powered Quadrotor by Habibe Gursoy Demir

    Published 2025-04-01
    “…This paper presents a comparison of the performances of metaheuristic methods such as Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) to design controllers and DC/DC buck converters for optimizing the energy consumption and path following error of a PEM fuel cell-powered quadrotor system. …”
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    Article
  19. 559

    Research on Impact of Planned Path Length and Yaw Cost on Collaborative Search of Unmanned Aerial Vehicle Swarms by Heng Zhang, Wenyue Meng, Yanan Liu, Guanyu Liu, Jian Zhang

    Published 2025-05-01
    “…To address the unclear impacts of a planned path length and yaw cost on search performance in large-scale Unmanned Aerial Vehicle (UAV) swarm collaborative search scenarios under complex and dynamic environments, a path grid determination algorithm is proposed, transforming the path-planning problem into an optimal waypoint selection problem, enabling UAVs to make rapid decisions using the Particle Swarm Optimization (PSO) algorithm. …”
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    Article
  20. 560