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  1. 1681

    Aerodynamic Optimization Method for Propeller Airfoil Based on DBO-BP and NSWOA by Changjing Guo, Zhiling Xu, Xiaoyan Yang, Hao Li

    Published 2024-11-01
    “…To address the issues of tedious optimization processes, insufficient fitting accuracy of surrogate models, and low optimization efficiency in drone propeller airfoil design, this paper proposes an aerodynamic optimization method for propeller airfoils based on DBO-BP (Dum Beetle Optimizer-Back-Propagation) and NSWOA (Non-Dominated Sorting Whale Optimization Algorithm). …”
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  2. 1682
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    A Comparison of the Black Hole Algorithm Against Conventional Training Strategies for Neural Networks by Péter Veres

    Published 2025-07-01
    “…Artificial Intelligence continues to demand robust and adaptable training methods for neural networks, particularly in scenarios involving limited computational resources or noisy, complex data. This study presents a comparative analysis of four training algorithms, Backpropagation, Genetic Algorithm, Black-hole Algorithm, and Particle Swarm Optimization, evaluated across both classification and regression tasks. …”
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  4. 1684

    Multilevel thresholding of color images using globally informed artificial bee colony algorithm by Ivona Brajević, Jelena Ignjatović

    Published 2025-07-01
    “…Abstract Multilevel image thresholding presents a computational challenge as the number of thresholds increases, requiring efficient optimization techniques. …”
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    Design of Periodic Neural Networks for Computational Investigations of Nonlinear Hepatitis C Virus Model Under Boozing by Abdul Mannan, Jamshaid Ul Rahman, Quaid Iqbal, Rubiqa Zulfiqar

    Published 2025-03-01
    “…We employ periodic neural networks, optimized using a hybrid genetic algorithm and the interior-point algorithm, to solve a system of six coupled nonlinear differential equations representing hepatitis C virus dynamics. …”
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  10. 1690

    Unmanned-Aerial-Vehicle Trajectory Planning for Reliable Edge Data Collection in Complex Environments by Zhengzhe Xiang, Fuli Ying, Xizi Xue, Xiaorui Peng, Yufei Zhang

    Published 2025-02-01
    “…However, existing UAV trajectory optimization algorithms often overlook the critical factor of the battery capacity, leading to potential mission failures or safety risks. …”
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    Application of Multi-Strategy Controlled Rime Algorithm in Path Planning for Delivery Robots by Haokai Lv, Qian Qian, Jiawen Pan, Miao Song, Yong Feng, Yingna Li

    Published 2025-07-01
    “…During the algorithm validation phase, comparative tests were conducted between two groups of algorithms, demonstrating their significant advantages in optimization capability, convergence speed, and stability. …”
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    Research on cutting mechanism and process optimization method of gear skiving by Peng Wang, Yuanchao Ni, Xiaoqiang Wu, Jiaxue Ji, Geng Li, Jiahao Wu

    Published 2025-02-01
    “…Furthermore, a prediction model of cutting force and cutting temperature is established using a neural network optimized by genetic algorithm. This prediction model allows for the construction of a multi-objective optimization model for the process parameters. …”
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  18. 1698
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    Wireless sensor node localization based on IPSO-MC by Yongyan LI, Jianping WU

    Published 2020-03-01
    “…To solve the problem of insufficient node positioning accuracy in wireless sensor networks,an algorithm based on improved particle swarm optimization by membrane computing (IPSO-MC) was proposed.Kent mapping was used to initialize the population and domain particles were introduced to improve the global optimization of the particle swarm.The weight factor and nonlinear extreme value perturbation were used to improve the local optimization ability of the particle swarm,and the Levy flight mechanism was used to optimize the individual position.Finally,the optimal solution of the particle swarm algorithm was obtained by the evolutionary rules of the membrane computing.Simulation experiments show that compared with the chicken flock algorithm,the improved particle swarm algorithm and the membrane computing,the proposed algorithm improves 3.24%,5.12% and 8.15% in the comparison of reference node ratio indicators,and the increase in the number of nodes indicators by 2.26%,7.82% and 9.81%,and the comparison of communication radius indicators increased by 2.15%,5.5% and 7.5%,respectively.This indicates that the algorithm has a good effect in node localization.…”
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