Showing 361 - 380 results of 3,188 for search '(( improve whole optimization algorithm ) OR ( improve while optimization algorithm ))', query time: 0.27s Refine Results
  1. 361

    Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

    Published 2024-09-01
    “…The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
    Get full text
    Article
  2. 362

    Optimizing high-speed train tracking intervals with an improved multi-objective grey wolf by Lin Yue, Meng Wang, Peng Wang, Jinchao Mu

    Published 2025-06-01
    “…To achieve multi-objective dynamic optimization, a novel train tracking operation calculation method is proposed, utilizing the improved grey wolf optimization algorithm (MOGWO). …”
    Get full text
    Article
  3. 363

    Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm by S. Bharath, A. Vasuki

    Published 2025-04-01
    “…By balancing exploration-exploitation using CSA while adapting search parameters through reinforcement learning, RL-CSA ensures scalability, improved DG utilization (98%), and better voltage stability (< 0.005 p.u.), making it a robust and intelligent alternative for modern smart grid optimization.…”
    Get full text
    Article
  4. 364

    Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

    Published 2023-02-01
    “… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
    Get full text
    Article
  5. 365

    Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

    Published 2025-06-01
    “…In this study, a new improved meta-heuristic algorithm is proposed for solving the energy building optimization (EBO) and also hybrid energy systems optimization considering uncertainty of conditioned surface area subjected to temperature control for BEO and renewable power and load uncertainties for hybrid system. …”
    Get full text
    Article
  6. 366

    Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm by Sydney Mutale, Yong Wang, De Tian

    Published 2025-07-01
    “…This study introduces a novel approach for minimizing assembly errors in wind turbine gearboxes using a hybrid optimization algorithm, Particle Swarm-Bacteria Foraging Optimization (PSBFO). …”
    Get full text
    Article
  7. 367

    Optimization method improvement for nonlinear constrained single objective system without mathematical models by HOU Gong-yu, XU Zhe-dong, LIU Xin, NIU Xiao-tong, WANG Qing-le

    Published 2018-11-01
    “…In addition, samples are needed to solve such system optimization problems. Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. …”
    Get full text
    Article
  8. 368

    5G-Practical Byzantine Fault Tolerance: An Improved PBFT Consensus Algorithm for the 5G Network by Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

    Published 2025-03-01
    “…With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant consensus algorithm with three ways to improve PBFT. …”
    Get full text
    Article
  9. 369
  10. 370

    Particle Swarm Optimization on Parallel Computers for Improving the Performance of a Gait Recognition System by Shahla A. Abdulqader, Hasmek A. Krekorian

    Published 2019-12-01
    “…In recent years, the gait recognition (GR) using particle swarm optimization (PSO) algorithm (OSO) has been execute very fast and accurate with single computer, but with the appearance of parallel computing (PC), it was necessary to use this technique to improve the results of GR. …”
    Get full text
    Article
  11. 371

    An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis by Yao Zhang, Xu Wang, Haohua Xiu, Wei Chen, Yongxin Ma, Guowu Wei, Lei Ren, Luquan Ren

    Published 2024-01-01
    “…Additionally, a hybrid grey wolf optimization and slime mould algorithm (GWO-SMA) is proposed to optimize the hidden layer bias of the improved ELM classifier. …”
    Get full text
    Article
  12. 372

    Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm by Kailiang Han, Yiming Hu, Dequan Zeng, Yinquan Yu, Lei Xiao, Jinwen Yang, Weidong Liu, Letian Gao

    Published 2024-11-01
    “…A multi-objective intelligent optimization algorithm-based attitude control strategy for magnetorheological semi-active suspension is proposed to address the vehicle attitude imbalance generated during steering and braking. …”
    Get full text
    Article
  13. 373

    Advanced strategies for the efficient optimization and control of industrial compressed air systems by D. Salomone-González

    Published 2025-06-01
    “…Real-time data transmission, powered by big data algorithms, enables continuous analysis to optimize the overall performance of the compressor plant. …”
    Get full text
    Article
  14. 374
  15. 375

    GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

    Published 2025-04-01
    “…Cross-scale shared convolution parameters and separated batch normalization techniques are used to optimize the detection head, achieving a lightweight design and improving the detection efficiency of the algorithm. …”
    Get full text
    Article
  16. 376

    GIRH-Unet: Improved Residual Tobacco Segmentation Algorithm Based on GhostNetV3-Unet by Jianhua Ye, Yunda Zhang, Pan Li, Ze Guo

    Published 2025-01-01
    “…Our approach utilizes an improved GhostNetV3 to bolster feature extraction capabilities. …”
    Get full text
    Article
  17. 377

    Edge detection of aerial images using artificial bee colony algorithm by Nurdan Akhan Baykan, Elif Deniz Yelmenoglu

    Published 2022-06-01
    “…In this paper, aerial images are used for edge information extraction by using Artificial Bee Colony (ABC) Optimization Algorithm. Procedures were performed on gray scale aerial images which are taken from RADIUS/DARPA-IU Fort Hood database. …”
    Get full text
    Article
  18. 378

    Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

    Published 2024-11-01
    “…[Methods]The YOLOv11-AP2S model enhanced the YOLOv11 algorithm by incorporating a series of improvements to its backbone network, neck, and head components. …”
    Get full text
    Article
  19. 379

    Fixed Depth Control Strategy for Remotely Operated Vehicle Based on Improved Model Predictive Control Algorithm by Shuo YANG, Honghui WANG, Xinyu LIU, Xin FANG, Guanghao LI, Guijie LIU

    Published 2025-06-01
    “…First, a nonlinear marine predator algorithm(NMPA) was introduced to optimize key control parameters of MPC, ensuring fast and precise depth tracking of ROVs in complex marine environments. …”
    Get full text
    Article
  20. 380

    Improved Aerial Surface Floating Object Detection and Classification Recognition Algorithm Based on YOLOv8n by Lili Song, Haixin Deng, Jianfeng Han, Xiongwei Gao

    Published 2025-03-01
    “…To address the aforementioned challenges, we proposed an improved YOLOv8-HSH algorithm based on YOLOv8n. The proposed algorithm introduces several key enhancements: (1) an enhanced HorBlock module to facilitate multi-gradient and multi-scale superposition, thereby intensifying critical floating object characteristics; (2) an optimized CBAM attention mechanism to mitigate background noise interference and substantially elevate detection accuracy; (3) the incorporation of a minor target recognition layer to augment the model’s capacity to discern floating objects of differing dimensions across various environments; and (4) the implementation of the WIoU loss function to enhance the model’s convergence rate and regression accuracy. …”
    Get full text
    Article