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  1. 1681

    Multi mobile agent itinerary planning based on network coverage and multi-objective discrete social spider optimization algorithm by Zhou-zhou LIU, Shi-ning LI

    Published 2017-06-01
    “…The multi mobile agent collaboration planning model was constructed based on the mobile agent load balancing and total network energy consumption index.In order to prolong the network lifetime,the network node dormancy mechanism based on WSN network coverage was put forward,using fewer worked nodes to meet the requirements of network coverage.According to the multi mobile agent collaborative planning technical features,the multi-objective discrete social spider optimization algorithm (MDSSO) with Pareto optimal solutions was designed.The interpolation learning and exchange variations particle updating strategy was redefined,and the optimal set size was adjusted dynamically,which helps to improve the accuracy of MDSSO.Simulation results show that the proposed algorithm can quickly give the WSN multi mobile agent path planning scheme,and compared with other schemes,the network total energy consumption has reduced by 15%,and the network lifetime has increased by 23%.…”
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  2. 1682

    Numerical Design Structure Matrix–Genetic Algorithm-Based Optimization Method for Design Process of Complex Civil Aircraft Systems by Qiucen Fan, Yanlong Han, An Zhang, Wenhao Bi

    Published 2024-12-01
    “…The algorithm NSGA-II is improved and verified with the flight control system design as a case study. …”
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  3. 1683
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  5. 1685

    An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

    Published 2025-04-01
    “…This operation also reduces the computational cost by decreasing the amount of required feature map channels, while maintaining the effectiveness of the feature representation. (3) he Minimum Point Distance Intersection over Union loss function is employed to optimize bounding box detection during model training. (4) to construct the overall network structure, the Layer-wise Adaptive Momentum Pruning algorithm is used for thinning.ResultsExperiments on the TinyPerson dataset demonstrate that IYFVMNet achieves a 46.3% precision, 30% recall, 29.3% mAP50, and 11.8% mAP50-95.DiscussionThe model exhibits higher performance in terms of accuracy and efficiency when compared to other benchmark models, which demonstrates the effectiveness of the improved algorithm (e.g., YOLO-SGF, Guo-Net, TRC-YOLO) in small-object detection and provides a reference for future research.…”
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  6. 1686
  7. 1687

    A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

    Published 2025-02-01
    “…To meet the demands of real-time and accurate defect detection, this paper introduces an optimization algorithm based on the GLV-YOLO model tailored for photodetector defect detection in manufacturing settings. …”
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  8. 1688

    Enhanced ANN-Based MPPT for Photovoltaic Systems: Integrating Metaheuristic and Analytical Algorithms for Optimal Performance Under Partial Shading by Alpaslan Demirci, Idriss Dagal, Said Mirza Tercan, Hasan Gundogdu, Musa Terkes, Umit Cali

    Published 2025-01-01
    “…The results demonstrate that the improved ANN-based MPPT algorithm consistently outperforms existing MPPT techniques, including the Perturb and Observe (P&O) and Grey Wolf Optimization (GWO), Harris Hawks Optimization (HHO), and Particle Swarm Optimization (PSO) methods. …”
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  9. 1689

    MODEL FOR THE FORMATION OF A PROJECT TEAM COMPOSITION BASED ON DISCRETE OPTIMIZATION METHODS by S.M. Beketov, M.V. Dergachev, S.G. Redko

    Published 2025-05-01
    “…The research is aimed at improving project management methods and models and may be useful for project managers, HR specialists and company management seeking to implement methods to optimize the composition of teams in the implementation of projects. …”
    Article
  10. 1690

    METAHEURISTIC-AI ENHANCED CUSTOM DEEP LEARNING NETWORK OPTIMIZED WITH SAND CAT SWARM ALGORITHM FOR ORAL CANCER DIAGNOSIS by Vinod Kumar Venkatesan, V Sujatha, Audithan Sivaraman, S Durga Devi, Praveen SR Konduri

    Published 2025-06-01
    “…The CNN architecture is designed to automatically extract discriminative features from images, while the SCSO algorithm fine-tunes crucial hyperparameters such as learning rate, batch size, and dropout rate to enhance model performance. …”
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  11. 1691
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  13. 1693

    Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

    Published 2025-02-01
    “…Abstract The relevance of the study is due to the growing number of diseases of the cerebrovascular system, in particular stroke, which is one of the leading causes of disability and mortality in the world. To improve stroke risk prediction models in terms of efficiency and interpretability, we propose to integrate modern machine learning algorithms and data dimensionality reduction methods, in particular XGBoost and optimized principal component analysis (PCA), which provide data structuring and increase processing speed, especially for large datasets. …”
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  14. 1694

    Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength by Jeonghyun Kim, Donwoo Lee

    Published 2025-06-01
    “…This study assesses the impact of hyperparameter optimization algorithms on the performance of machine learning-based concrete compressive strength prediction models. …”
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  15. 1695

    Hyperparameter Optimization for Problem-Based Custom CNN Architectures Using a Smart Grid Search Method by H. Aktas

    Published 2025-01-01
    “…To classify the ripe and unripe pistachios with a small-sized and high test accuracy model, a two-layer CNN architecture’s hyperparameters were optimized with the proposed algorithm. …”
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  16. 1696

    Synergistic integration of refined pelican optimization algorithm and deep neural networks for autonomous vehicle control in edge computing architectures by Fude Duan, Bing Han, Xiongzhu Bu

    Published 2025-06-01
    “…The chief contributions of the present study have been threefold: (1) the improvement of a particular autonomous driving method optimized for mobile edge computing platforms; (2) the arrangement of an optimized MobileNet method employing the RPO algorithm that uses LiDAR sensor data for effective object recognition and path design; and (3) the construction of an indoor vehicle prototype by mean of a microcontroller and LiDAR sensors, after a comprehensive performance evaluation of inference models, and analyzing the trade-offs between input size and computational effectiveness. …”
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  17. 1697

    Prediction of chloride concentration in concrete under multi-salt environment: Optimization of integrated algorithm based on MSCPO and interpretability analysis by Daming Luo, Kanglei Du, Ditao Niu

    Published 2025-03-01
    “…The Improved Mixture Self-Adaptation Crested Porcupine Optimizer (MSCPO) optimized hyperparameters for XGBoost, LightGBM, and Catboost models separately. …”
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  18. 1698

    Optimization of Structural Parameters and Cavitation Suppression in Control Valves Based on P-WOA by W. Li, S. Li, J. Hou, L. Yang, Y. Tian

    Published 2025-06-01
    “…Boosting method integrates reinforcement learning PPO with the whale optimization algorithm (WOA) to form the P-WOA model. …”
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