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Showing 141 - 160 results of 266 for search '(improved OR improve) grey wolf optimization algorithm', query time: 0.14s Refine Results
  1. 141
  2. 142

    A Global Coverage Path Planning Method for Multi-UAV Maritime Surveillance in Complex Obstacle Environments by Yiyuan Li, Weiyi Chen, Bing Fu, Zhonghong Wu, Lingjun Hao

    Published 2024-12-01
    “…Secondly, a method for calculating obstacle-avoidance path costs based on the Voronoi diagram is proposed, laying the foundation for obtaining the optimal access order. Thirdly, an improved discrete grey wolf optimizer (IDGWO) algorithm integrated with variable neighborhood search (VNS) operations is proposed to perform task assignment for multiple UAVs and achieve workload balancing. …”
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  3. 143

    An Investigation into the Rescue-Path Planning Algorithm for Multiple Mine Rescue Teams Based on FA-MDPSO and an Improved Force-Directed Layout by Qiangyu Zheng, Peijiang Ding, Zhixin Qin, Zhenguo Yan

    Published 2025-05-01
    “…Subsequently, the hyperparameters of MDPSO (Multiple Constraints Discrete Particle Swarm Optimisation) were optimised by means of four intelligent algorithms—ACO (Ant Colony Optimization), FA (Firefly Algorithm), GWO (Grey Wolf Optimizer) and WOA (Whale Optimization Algorithm). …”
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  4. 144

    Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment by Pei Zhu, Shize Jiang, Jiangao Zhang, Ziheng Xu, Zhi Sun, Quan Shao

    Published 2025-02-01
    “…In this process, the study considers only the use of fire-extinguishing balls as the fire suppressant for the UAVs. The improved multi-population grey wolf optimization (MP–GWO) algorithm and non-Dominated sorting genetic algorithm II (NSGA-II) were designed to solve the path planning and task allocation models, respectively. …”
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  5. 145

    Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

    Published 2025-03-01
    “…The conventional methods, such as grey wolf optimization (GWO), fail to address real-time user demand and dynamic factors like fluctuating grid loads and environmental impact. …”
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  6. 146

    A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions by Boyan Huang, Kai Song, Shulin Jiang, Zhenqing Zhao, Zhiqiang Zhang, Cong Li, Jiawen Sun

    Published 2024-12-01
    “…Both the simulations and the experimental results indicate that the proposed algorithm outperforms particle swarm optimization (PSO) and grey wolf optimization (GWO) in terms of convergence velocity, tracking precision, and the reduction in iteration power oscillation magnitude.…”
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  7. 147

    Prediction of Provincial Energy Consumption Intensity and Estimation of Carbon Emission Reduction Potential Based on PSO-GWO by Fugui DONG, Meijuan XIA, Wanying LI

    Published 2023-09-01
    “…An energy intensity learning curve was constructed, which contains such three factors as economy, technology input and scale effect, and the grey wolf algorithm was used to improve the particle swarm optimization algorithm to optimize the fitting curves. …”
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  8. 148

    CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

    Published 2025-03-01
    “…Moreover, the performance of IHO was proven to be optimal compared to HO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and Sparrow Search Algorithm (SSA) by calculating twelve test functions. …”
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  9. 149

    Spaceborne THz-ISAR Imaging of Space Target with Joint Motion Compensation Based on FrFT and GWO by Ao Zhou, Qi Yang, Zhian Yuan, Hongqiang Wang, Jun Yi, Shuangxun Li

    Published 2025-06-01
    “…Finally, with SWE serving as the fitness function, the Grey Wolf Optimizer (GWO) algorithm is used to search for optimal estimated translation parameters. …”
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  10. 150
  11. 151

    Logarithmic mean optimization a metaheuristic algorithm for global and case specific energy optimization by Idriss Dagal, Ambe Harrison, Wulfran Fendzi Mbasso, Fritz Nguemo Kemdoum, Mohammad Khishe, Pradeep Jangir, Aseel Smerat, Saad F. Al-Gahtani, Z. M.S. Elbarbary, Emmanuel Fendzi Donfack, Hassan Abouobaida

    Published 2025-05-01
    “…LMO leverages logarithmic mean operations to achieve a superior balance between exploration and exploitation. The algorithm’s performance was benchmarked against six established methods—Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Grey Wolf Optimizer (GWO), Cuckoo Search Algorithm (CSA), and Firefly Algorithm (FA)—using the CEC 2017 suite of 23 high-dimensional functions. …”
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  12. 152

    Discrete Sizing Optimization of Steel Structures Using Modified Fireworks Algorithm by Navid Seraji, Mehdi Babaei

    Published 2025-01-01
    “…A total of six benchmark structures including a 10-bar truss, a 25-bar truss, a 582-bar tower truss, a two-bay three-story frame, a one-bay 10-story frame, and a three-bay 24-story frame are chosen from previous studies for the optimization. In addition, a comparison is presented between the results of MoFWA with FWA and other optimization methods such as modified sine-cosine algorithm (MSCA), newton meta-heuristic algorithm (NMA), improved grey wolf optimizer (GWOM), enhanced whale optimization algorithm (EWOA), switching teams algorithm (STA), MHBMO, artificial bee colony (ABC), school-based optimization (SBO), teaching-learning based optimization (TLBO), design-driven harmony search (DDHS), and inscribed hyperspheres (IHS). …”
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  13. 153

    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
    “…The simulation results demonstrate that for sparse linear arrays, planar rectangular arrays, and multi-ring concentric circular arrays, the proposed algorithm achieves a sidelobe level (SLL) reduction exceeding 0.24 dB compared to conventional approaches, including the grey wolf optimizer (GWO), the whale optimization algorithm (WOA), and classical PSO. …”
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  14. 154

    Optimizing Kernel Extreme Learning Machine based on a Enhanced Adaptive Whale Optimization Algorithm for classification task. by ZeSheng Lin

    Published 2025-01-01
    “…Secondly, the WOA's position update formula was modified by incorporating inertia weight ω and enhancing convergence factor α, thus improving its capability for local search. Furthermore, inspired by the grey wolf optimization algorithm, use 3 excellent particle surround strategies instead of the original random selecting particles. …”
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  15. 155

    Chameleon swarm algorithm with Morlet wavelet mutation for superior optimization performance by Vipan Kusla, Gurbinder Singh Brar, Harpreet Kaur, Ramandeep Sandhu, Chander Prabha, Md. Mehedi Hassan, Shahab Abdulla, Md Rittique Alam, Samah Alshathri, Walid El-Shafai

    Published 2025-04-01
    “…Five performance metrics—average energy consumption, total energy consumption, total residual energy, dead node and cluster head frequency are taken into consideration when evaluating the performances against state-of-the-art algorithms. For nine different simulation scenarios, the proposed algorithm mCSAMWL outperforms the Atom Search Optimization (ASO), Hybrid Particle Swarm Optimization and Grey Wolf Optimization (PSO-GWO), Bald Eagle Search Algorithm (BES), the African Vulture Optimization Algorithm (AVOA), and the Chameleon Swarm Algorithm (CSA) in terms of average energy consumption and total energy consumption by 50.9%, 52.6%, 45%, 42.4%, 50.1% and 51.4%, 53.3%, 45.6%, 42.4%, 50.7%.…”
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  16. 156

    Optimizing Photovoltaic Panel Performance: A Comparative Study of Meta-Heuristic Algorithms by M. Sundar Rajan

    Published 2024-06-01
    “…This method was compared against other well-known algorithms such as Artificial Bee Colony (ABC), Dragonfly Algorithm (DA), Grey Wolf Optimizer (GWO), Cuckoo Search (CS), Composite Grey Wolf Optimizer (CGWO), and the standalone PSO and GWO methods. …”
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  17. 157

    Comparative Analysis of Optimization Algorithms to Enhance WPGSs Performance: Malaysia Case Study by Hussein Shutari, Taib Ibrahim, Nursyarizal Bin Mohd Nor, Hakim Abdulrab, Yahya Z. Alharthi, Mohammad Faridun Naim Tajuddin, Maveeya Baba

    Published 2024-01-01
    “…The growing interest in wind power and its expanding integration into the electrical power grid necessitate significant efforts to enhance the efficiency and performance of wind power generation Systems (WPGS) through optimized design and operation. This paper investigates the implementation of five optimization algorithms:sine cosine algorithm (SCA), grey wolf optimizer (GWO), particle swarm optimizer (PSO), transient search optimization (TSO), and a hybrid sine cosine algorithm-transient search optimizer (HSCATSO), to optimally design control schemes (ODCSs) of frequency converters within grid-connected WPGS. …”
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  18. 158

    An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions by Md.Al Imran Fahim, Md.Salah Uddin Yusuf, Monira Islam, Munshi Jawad Ibne Azad

    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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  19. 159

    Various optimization algorithms for efficient placement and sizing of photovoltaic distributed generations in different networks. by Ahmed A Zaki Diab, Fayza S Mahmoud, Hamdy M Sultan, Abou-Hashema M El-Sayed, Mohamed A Ismeil, Omar Makram Kamel

    Published 2025-01-01
    “…Various optimization techniques, namely Salp Swarm Algorithm (SSA), Marine Predictor Algorithm (MPA), Grey Wolf Optimizer (GWO), Improved Grey Wolf Optimizer (IGWO), and Seagull Optimization Algorithm (SOA), have been applied to achieve optimal allocation and sizing of RDGs in radial distributed systems (RDS). …”
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  20. 160

    Research on Path Planning Multiple Mobile Robots Based on the LAPGWO Algorithm by Wan Xu, Dongting Liu, Ao Nie, Junqi Wang, Shijie Liu

    Published 2025-05-01
    “…Given that the traditional optimization algorithm (GWO) often encounters problems like local optimum, and the convergence efficiency is not satisfactory in the path planning task of multiple mobile robots, an improved grey wolf optimization algorithm (LAPGWO) based on the combination of the logistic chaotic mapping and the artificial potential field method (APF) is proposed. …”
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