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  1. 1741

    Shuffled Puma Optimizer for Parameter Extraction and Sensitivity Analysis in Photovoltaic Models by En-Jui Liu, Rou-Wen Chen, Qing-An Wang, Wan-Ling Lu

    Published 2025-07-01
    “…To address this challenge, a novel metaheuristic algorithm called shuffled puma optimizer (SPO) is deployed to perform parameter extraction and optimal configuration identification across four PV models. …”
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  2. 1742

    FPGA-Based Particle Swarm Collaborative Target Localization Algorithm for UAV Swarms by Chuanhao Zhang, Changsheng Li, Zhipeng Chen, Haojie Li, Hang Yu

    Published 2025-04-01
    “…By leveraging the unique computational capabilities of FPGA, the proposed algorithm integrates optimization strategies, including particle mutation, variable crossover probabilities, and adjustable weights. …”
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  3. 1743

    Maximizing efficiency and performance of water distribution systems through the implementation of optimization algorithms: A comprehensive analysis of valve and chlorine booster pl... by Mohamadreza Najarzadegan, Mehrtash Eskandaripour

    Published 2025-02-01
    “…The results demonstrate a 15 % reduction in average pressure fluctuations and a 20 % improvement in chlorine residual uniformity, validating the effectiveness of the integrated optimization approach. Additionally, the SMA algorithm outperformed GA in terms of computational efficiency and solution quality, achieving a 12 % lower error margin and a 33 % reduction in computational time. …”
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    House Swallow Optimizer: A New Meta-Heuristic Algorithm and Its Application for DOA Estimation of Broadband Signal in Vector Hydrophone Array by Jie Dong, Lifu Wang, Shuhui Qiao, Peng Wang, Xiuhui Tan

    Published 2025-01-01
    “…The experimental outcomes prove that HSO has a strong ability to balance exploration and development, with out-performance over comparative algorithms. In order to verify the engineering application potential of the optimization algorithm proposed in this paper, aiming at the problems of large estimation error, high computational complexity and low accuracy in the DOA estimation of broadband signal of vector hydrophone array, the HSO algorithm is applied to the ML algorithm, and the DOA estimation of broadband signal is successfully carried out. …”
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    A Solution Method for Non-Linear Underdetermined Equation Systems in Grounding Grid Corrosion Diagnosis Based on an Enhanced Hippopotamus Optimization Algorithm by Jinhe Chen, Jianyu Qi, Yiyang Ao, Keying Wang, Xin Song

    Published 2025-07-01
    “…Conventional diagnosis must fit high-dimensional electrical data to a physical model, typically yielding a nonlinear under-determined system fraught with computational burden and uncertainty. We propose the Enhanced Biomimetic Hippopotamus Optimization (EBOHO) algorithm, which distills the river-dwelling hippo’s ecological wisdom into three synergistic strategies: a beta-function herd seeding that replicates the genetic diversity of juvenile hippos diffusing through wetlands, an elite–mean cooperative foraging rule that echoes the way dominant bulls steer the herd toward nutrient-rich pastures, and a lens imaging opposition maneuver inspired by moonlit water reflections that spawn mirror candidates to avert premature convergence. …”
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  15. 1755

    RETRACTED: Intelligent power grid energy supply forecasting and economic operation management using the snake optimizer algorithm with Bigur-attention model by Lingling Cui, Jiacheng Liao

    Published 2023-09-01
    “…In the model training phase, the Snake Optimizer (SO) algorithm-optimized Bigru-Attention model combines time series, spatial features, and optimization features to build a comprehensive prediction model. …”
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    A Novel Adaptive Fine-Tuning Algorithm for Multimodal Models: Self-Optimizing Classification and Selection of High-Quality Datasets in Remote Sensing by Yi Ren, Tianyi Zhang, Zhixiong Han, Weibin Li, Zhiyang Wang, Wenbo Ji, Chenhao Qin, Licheng Jiao

    Published 2025-05-01
    “…However, the vast amount of image data in this field presents a challenge in selecting high-quality multimodal data, which are essential for saving computational resources and time. Therefore, we propose an adaptive fine-tuning algorithm for multimodal large models. …”
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