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  1. 1121

    Research on the Optimization Method of Visual Sensor Calibration Combining Convex Lens Imaging with the Bionic Algorithm of Wolf Pack Predation by Qingdong Wu, Jijun Miao, Zhaohui Liu, Jiaxiu Chang

    Published 2024-09-01
    “…The comparative experimental results show that the average reprojection errors of the simulated annealing algorithm, Zhang’s calibration method, the sparrow search algorithm, the particle swarm optimization algorithm, bionic algorithm of Wolf Pack Predation, and the algorithm proposed in this paper (CLI-WPP) are 0.42986500, 0.28847656, 0.23543161, 0.219342495, 0.10637477, and 0.06615037, respectively. …”
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    Article
  2. 1122

    Optimization of electric vehicle charging facility layout considering the enhancement of renewable energy consumption capacity and improvement of PSO algorithm by Di Zheng, Baobao Zheng

    Published 2025-04-01
    “…To deal with the optimization model, the particle swarm optimization is adopted and improved in three aspects. …”
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    Article
  3. 1123

    Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

    Published 2025-01-01
    “…Moreover, comparative analyses of various optimization methods on the custom-built dataset reveal that the ant colony optimization algorithm markedly outperforms the simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO). …”
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    Article
  4. 1124

    TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables) by QI Junyan, CHE Yuhao, WANG Lei, YUAN Ruifu

    Published 2025-05-01
    “…Experimental results showed that: ① Compared with the Slime Mould Algorithm (SMA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Sparrow Search Algorithm (SSA), the ISMA optimization strategy demonstrated better convergence speed and optimization ability in multiple benchmark function tests. ② In the stress prediction experiment, ablation experiments verified the necessity of TCN, LSTM, and MHSA modules. ③ The ISMA-optimized TCN-LSTM-MHSA model outperformed mainstream prediction models such as BP and GRU in MAE, RMSE, and R2 metrics, showing higher prediction accuracy and stability.…”
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    Article
  5. 1125

    Multi-Peak Photovoltaic Maximum Power Point Tracking Method Based on Honey Badger Algorithm Under Localized Shading Conditions by Qianjin Gui, Lei Wang, Chao Ding, Wenfa Xu, Xiaoyang Li, Feilong Yu, Haisen Wang

    Published 2025-03-01
    “…The performance of this method is also compared and analyzed with the traditional MPPT methods based on the perturbation observation (P&O) method and Particle Swarm Optimization (PSO) algorithm. The experimental results have proven that, compared with the MPPT methods based on P&O and PSO, the proposed multi-peak MPPT method based on the HBA algorithm has a faster tracking speed, higher tracking accuracy, and fewer iterations.…”
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    Article
  6. 1126

    Effective Modeling of Photovoltaic Modules Using Sailfish Optimizer by Mohammed Bilal Danoune, A. Djafour, Youcef Rehouma, A. Degla, Zied Dress

    Published 2023-02-01
    “…Moreover, to show the efficacy of the algorithm, the results are compared with some literature techniques such as Salp-Swarm-Optimizer (SSA), Whale Optimization (WOA), Artificial-Bee-Colony (ABC), and Particle-Swarm Optimization (PSO) methods. …”
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    Article
  7. 1127

    Hybrid optimized data aggregation for fog computing devices in internet of things by M. Jalasri, S. Manikandan, Arthur Davis Nicholas, S. Gobimohan, Naarisetti Srinivasa Rao

    Published 2024-05-01
    “…In this work, a new and novel hybrid optimization technique based on TABU Search (TS), Particle Swarm Optimization (PSO), and River Formation Dynamics (RFD) algorithms were proposed. …”
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    Article
  8. 1128

    Multi-objective optimization and parameter sensitivity study on microreactor nuclear power systems by Ersheng You, Yiyi Li, Jianjun Xu, Dianchuan Xing, Haochun Zhang

    Published 2025-10-01
    “…Aiming at the MRNPS based on Brayton cycles, the particle swarm optimization (PSO) method was used to carry out the optimization calculation and analysis of three target parameters: system thermal efficiency, power-to-weight ratio and radiator heat removal area. …”
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    Article
  9. 1129

    A Thinning Method of Linear And Planar Array Antennas To Reduce SLL of Radiation Pattern By GWO And ICA Algorithms by H. Rezagholizadeh, D. Gharavian

    Published 2018-12-01
    “…Thinning is performed using Genetic, Particle Swarm, Imperialist Competitive and Grey Wolf algorithms. …”
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    Article
  10. 1130
  11. 1131

    A Review of QoS-Driven Task Scheduling Algorithms and Their Impact on Data Quality in Process Management by Anupam Yadav, Ashish Sharma

    Published 2025-02-01
    “…According to this study, the scheduling algorithms that are used by researchers 80% of the time include the genetic algorithm in bio-inspired systems and particle swarm optimization in swarm intelligence. …”
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    Article
  12. 1132

    Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance by Mahmoud M. Eid, Kamal ElDahshan, Abdelatif H. Abouali, Alaa Tharwat

    Published 2025-02-01
    “…The first set uses synthetic datasets to compare four optimization algorithmsParticle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and the Sine–Cosine Algorithm (SCA)—to determine which one best identifies features related to the target feature. …”
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    Article
  13. 1133

    A Comparative Analysis of Swarm Intelligence Techniques for Feature Selection in Cancer Classification by Chellamuthu Gunavathi, Kandasamy Premalatha

    Published 2014-01-01
    “…In SFLLF, the Lévy flight is included to avoid premature convergence of shuffled frog leaping (SFL) algorithm. The SI techniques such as particle swarm optimization (PSO), cuckoo search (CS), SFL, and SFLLF are used for feature selection which identifies informative genes for classification. …”
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    Article
  14. 1134

    An Intrusion Detection System Based on Deep Learning and Metaheuristic Algorithm for IOT by Bahman Sanjabi, Mahmood Ahmadi

    Published 2024-04-01
    “…In this paper, a method is presented that uses meta-heuristic algorithms such as genetic algorithm, particle swarm optimization, artificial bee colony and gray wolf to find the optimal hyperparameters for the deep learning network and the intrusion detection system is created based on these hyperparameters. …”
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    Article
  15. 1135

    A metaheuristic optimization framework inspired by virus mutations and its ability to optimize the structural design of 2D and 3D steel frames compared to other methods by Mehdi Ghasri, Hamid Reza Karimi, Abdolhamid Salarnia

    Published 2025-06-01
    “…MVPO integrates population-based exploration, simulating viral spread through intra-community interactions (guided by wavelet functions to model transmission variability) and inter-community propagation, with a two-phase mutation strategy: the first phase enhances global exploration via elongated search steps during accelerated spread, while the second phase introduces structural perturbations to escape local optima. The algorithm’s efficacy is evaluated through three benchmark problems, two planar (2D) frames and a three-dimensional (3D) space frame, with comparisons against established methods (e.g., particle swarm optimization, cuckoo search) and contemporary algorithms (e.g., marine predators algorithm, pelican optimization algorithm). …”
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    Article
  16. 1136

    Multi-objective coordinated control and optimization for photovoltaic microgrid scheduling by Da Yu, Kai Hou, Xu Lin, Guoyang Cai, Xin Shan, Weihua Wang

    Published 2025-06-01
    “…This paper proposes a multi-objective coordinated control and optimization system for PV microgrids. To address the challenges of slow convergence and local optima in traditional PV microgrid scheduling methods, this study introduced an improved multiple objective particle swarm optimization (IMOPSO) algorithm that integrates an adaptive inertia weight adjustment strategy based on optimal similarity and a multi-directional iterative Pareto solution archive update mechanism. …”
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    Article
  17. 1137

    AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

    Published 2025-06-01
    “…Results Simulation results demonstrate that the ISSA significantly outperforms the original SSA and other state-of-the-art algorithms, such as particle swarm optimization (PSO), differential evolution (DE), artificial bee colony (ABC), and whale optimization algorithm (WOA). …”
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    Article
  18. 1138

    An Optimized Closed-Loop Z-Source Inverter for Wind Energy Generation System Using Opposition-based Sine Cosine Algorithm by Sweta Kumari, Rajib Kumar Mandal

    Published 2024-05-01
    “…PI tuning for closed-loop ZSI is taken care of with the use of particle swarm optimization (PSO), the sine-cosine algorithm (SCA), and the opposition-based sine-cosine algorithm (OB-SCA). …”
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    Article
  19. 1139
  20. 1140

    Research on the construction of English vocabulary learning recommendation system based on multi-objective crow search algorithm by Mengli Li

    Published 2025-12-01
    “…Regarding the experiments, we compared MOCSO with traditional single - objective optimization algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). 56.4 % of users believe that the recommended vocabulary content meets their deep learning needs, while 18.2 % of learners hope that the system can further improve the practical application ability of vocabulary. …”
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    Article