Showing 761 - 780 results of 14,154 for search '(improved OR improve) model algorithm', query time: 0.32s Refine Results
  1. 761

    Improving 3D Reconstruction Through RGB-D Sensor Noise Modeling by Fahira Afzal Maken, Sundaram Muthu, Chuong Nguyen, Changming Sun, Jinguang Tong, Shan Wang, Russell Tsuchida, David Howard, Simon Dunstall, Lars Petersson

    Published 2025-02-01
    “…We collect a high-resolution RGB-D dataset and apply our noise model to improve tracking and produce higher-resolution 3D models.…”
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    Article
  2. 762
  3. 763

    Combining CFD and AI/ML Modeling to Improve the Performance of Polypropylene Fluidized Bed Reactors by Nayef Ghasem

    Published 2024-12-01
    “…COMSOL Multiphysics 6.2<sup>®</sup> solves a 2D multiphase CFD model for the reactor’s complex gas–solid interactions and fluid flows. …”
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    Article
  4. 764

    Construction of teaching quality evaluation model of online dance teaching course based on improved PSO-BPNN by Jin Ben, Li Hanwen

    Published 2025-05-01
    “…Based on this evaluation model, both teachers and students can receive feedback on teaching and learning processes, thereby improving teaching methods, meeting personalized needs of students, and enhancing learning outcomes. …”
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    Article
  5. 765

    Optimal Allocation of Hydrogen Storage Capacity Based on Improved Cat Swarm Optimization by Zhenda HU, Wenjin JIANG, Linyao ZHANG, Xiaodong YANG, Yichao ZOU, Kai WANG

    Published 2023-08-01
    “…The feasibility of using the improved cat swarm algorithm to solve the capacity optimization configuration model of hydrogen storage system was verified through numerical examples, and the rationality of the proposed hydrogen storage system capacity optimization configuration model was also demonstrated.…”
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    Article
  6. 766

    An Energy Management Optimization Strategy for Regional Power Grid Energy Storage System Based on Improved Artificial Bee Colony Algorithm by Ziqi WANG, Huiyuan ZHANG, Jun XU, Jiehui CHENG

    Published 2022-09-01
    “…In the process of solving the model, an improved artificial bee colony (IABC) algorithm is proposed, and simulation is designed out according to the structure and operation characteristics of the Turpan regional grid. …”
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    Article
  7. 767

    FAULT DIAGNOSIS METHOD OF SUBMERSIBLE SEWAGE PUMP BASED ON IMPROVED HOPFIELD NEURAL NETWORK by WANG Hui, LI NanQi, YANG ZhiPeng, ZHAO GuoChao, TIAN LiYong

    Published 2022-01-01
    “…The connection weights of HNN neural network were optimized by particle swarm optimization(PSO) algorithm to improve the global convergence ability of the improved neural network, and the improved HNN neural network model was obtained. …”
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    Article
  8. 768

    Research on Springback Compensation Method of Roll Forming Based on Improved Fuzzy PID Control by Tengqiang Wang, Yingping Qian, Wengkang Fang, Dongqiao Zhang, Huanqi Weng, Yiran Jiang

    Published 2025-03-01
    “…This demonstrates that the proposed springback compensation strategy for circular rolling effectively improves the accuracy of circular rolling.…”
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    Article
  9. 769

    Fog node intrusion detection and response based on SVMIF and INSGA-II algorithm by Zhuojun Luo

    Published 2025-12-01
    “…Additionally, modified particle swarm optimization was employed to optimize the model's parameters. To have a response behavior for protection when intrusion is detected, the study designed a fog node intrusion response method based on security policy decision and used improved non-dominated sorting genetic algorithms-II to select a more appropriate security decision. …”
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    Article
  10. 770

    Multi-UAV path planning considering multiple energy consumptions via an improved bee foraging learning particle swarm optimization algorithm by Yuanhang Qi, Haoran Jiang, Gewen Huang, Liang Yang, Fujie Wang, Yunjian Xu

    Published 2025-04-01
    “…To tackle the MUAVPP-MEC, this study proposes an improved Bee Foraging Learning Particle Swarm Optimization algorithm (IBFLPSO), which integrates the bee-foraging algorithm into the particle swarm optimization framework. …”
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    Article
  11. 771

    EAD-YOLOv10: Lightweight Steel Surface Defect Detection Algorithm Research Based on YOLOv10 Improvement by Hu Haoyan, Tong Jinwu, Wang Haibin, Lu Xinyun

    Published 2025-01-01
    “…The experimental results show that the improved EAD-YOLOv10 network model achieves an average precision of 94.2% for detecting six types of defects in the NEU-DET dataset, which is an improvement of 7.6% over the baseline model, with a 9.75% reduction in model size and a 12.5% decrease in computational load, outperforming other mainstream object detection algorithms and meeting the requirements for SD detection in industrial production. …”
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  12. 772
  13. 773

    RSM-YOLOv11: Lightweight Steel Surface Defect Segmentation Algorithm Research Based on YOLOv11 Improvement by Zenghai Shan, Hu Haoyan, Changjian Zhu, Shaowen Du, Hongtao Jing, Wang Haibin

    Published 2025-01-01
    “…To address these issues, this paper proposes an improved YOLOv11 segmentation model, RSM-YOLOv11. The Space-to-Depth Convolution (SPD-Conv) module is introduced to replace the traditional convolutional layer. …”
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  14. 774
  15. 775

    Small target detection algorithm based on SAHI-Improved-YOLOv8 for UAV imagery: A case study of tree pit detection by Xiuhao Liang, Jun Xiang, Sheng Qin, Yundan Xiao, Lifen Chen, Dongxia Zou, Honglun Ma, Dong Huang, Yongxin Huang, Wei Wei

    Published 2025-12-01
    “…The accuracy of identification and positioning can be improved by using the SAHI via cutting high-resolution UAV imagery into slices that match the detection model, avoiding the loss of small target detail caused by direct downsampling. …”
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  16. 776

    Prediction Analysis of College Students’ Physical Activity Behavior by Improving Gray Wolf Algorithm and Support Vector Machine by Minjian Wang

    Published 2022-01-01
    “…A nonlinear decreasing convergence factor strategy and an inertia weight strategy are introduced to improve the gray wolf optimization algorithm, which is used to determine the SVM parameters for the purpose of improving the model accuracy. …”
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    Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

    Published 2025-09-01
    “…The proposed explainable artificial intelligence feature selection method was compared to conventional feature selection techniques, including mutual information, chi-square coefficient, maximal information coefficient, Fisher separation criterion and variance thresholding. Results showed improved accuracy (92.62 % Random forest, 90.16 % Support vector machine, 83.61 % K-nearest neighbours, and 81.97 % Naïve Bayes) and a reduction in the number of model parameters and memory usage (7.22 × 107 Random forest, 6.23 × 103 Support vector machine, 3.64 × 104 K-nearest neighbours and 1.88 × 102 Naïve Bayes) compared to using all features. …”
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  20. 780