Showing 3,781 - 3,800 results of 5,620 for search 'while (optimizer OR optimize) algorithm', query time: 0.21s Refine Results
  1. 3781
  2. 3782

    Estimation of Leaf Chlorophyll Content of Maize from Hyperspectral Data Using E2D-COS Feature Selection, Deep Neural Network, and Transfer Learning by Riqiang Chen, Lipeng Ren, Guijun Yang, Zhida Cheng, Dan Zhao, Chengjian Zhang, Haikuan Feng, Haitang Hu, Hao Yang

    Published 2025-05-01
    “…Leaf chlorophyll content (LCC) serves as a vital biochemical indicator of photosynthetic activity and nitrogen status, critical for precision agriculture to optimize crop management. While UAV-based hyperspectral sensing offers maize LCC estimation potential, current methods struggle with overlapping spectral bands and suboptimal model accuracy. …”
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    Article
  3. 3783

    Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network by Rekha, Ritu Garg

    Published 2023-03-01
    “…In this article, we propose an optimization algorithm, based on meta-heuristic, to enhance the energy efficiency of amplify and forward relay IoT networks. …”
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    Article
  4. 3784

    Selection Based on Colony Fitness for Differential Evolution by Zi Ming, Yang Li, Shijie Peng, Xuechao Wu, Jinyi Guo

    Published 2018-01-01
    “…Selection based on the first version of the colony is embodied in DE/rand/1, a basic DE algorithm, while selection based on the second version is used in CoBiDE, a state-of-the-art DE algorithm. …”
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    Article
  5. 3785

    Energy-efficient power control for two-tier femtocell networks with block-fading channels by Zhixin Liu, Jieshuai Wu, Yang Liu, Hongjiu Yang, Jianfeng Guan, Yu Wang

    Published 2017-05-01
    “…A distributed iterative algorithm is proposed to obtain the optimal power solution. …”
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    Article
  6. 3786

    ROITP: Road Obstacle-Involved Trajectory Planner for Autonomous Trucks by Yechen Qin, Yiwei Huang, Wenhao Yu, Hong Wang

    Published 2025-02-01
    “…The planner categorizes road obstacles using a learning-based algorithm. A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics. …”
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    Article
  7. 3787

    Application of the Mean-shift Segmentation Parameters Estimator (MSPE) to VHSR satellite images: Tetuan-Morocco by O. Benarchid, N. Raissouni, J.A. Sobrino, A. El Ayyan

    Published 2015-06-01
    “…<p>Image segmentation is considered as crucial step dealing with Object-Based Image Analysis (OBIA) and different segmentation results could be achieved by combining possible parameters values. Optimal parameters selection is usually carried out on the basis of visual interpretation; therefore, defining optimal combinations is a challenging task. …”
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    Article
  8. 3788

    Improving inverter efficiency for electric vehicles: Experimental validation of the neural network-based SHE technique using RT-LAB by Seyf Eddine Bechekir, Mokhtaria Jbilou, Mostefa Brahami, Fatima Zohra Boudjella, Imen Souhila Bousmaha, Mimouna Oukli, Said Nemmich

    Published 2025-05-01
    “…MATLAB/Simulink simulations and experimental results on the RT-LAB simulator confirm the algorithm’s capability to calculate optimal switching angles and produce high-performance PWM waveforms. …”
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    Article
  9. 3789

    Implementation of VR application in cultural and tourism integration under the background of smart city and IoT by Wei Huang

    Published 2025-12-01
    “…In terms of system performance, the optimized virtual roaming system maintained stable memory and CPU usage while reducing GPU load by over 20 % and increasing the FPS from 30 fps to 44.6 fps. …”
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    Article
  10. 3790

    UAV Robust Strategy Control Based on MAS by Jian Han, Changhong Wang, Guoxing Yi

    Published 2014-01-01
    “…After simulation, the MAS has been proved to be able to promote the success ratio and raise the robustness, while realizing feasibility of coordinated flight and optimality of cooperative mission.…”
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    Article
  11. 3791

    An Approach to Finding a Robust Deep Learning Model by Alexey Boldyrev, Fedor Ratnikov, Andrey Shevelev

    Published 2025-01-01
    “…This approach, supplemented with a model selection algorithm designed as a meta-algorithm, is versatile and applicable to any machine learning model, provided that it is appropriate for the task at hand. …”
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    Article
  12. 3792

    HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks by Luca Marchetti, Rosario Lombardo, Corrado Priami

    Published 2017-01-01
    “…HSimulator provides optimized implementation of a set of widespread state-of-the-art stochastic, deterministic, and hybrid simulation strategies including the first publicly available implementation of the Hybrid Rejection-based Stochastic Simulation Algorithm (HRSSA). …”
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    Article
  13. 3793

    Joint Adaptive Modulation and Power Control Scheme for Energy Efficient FSO-based Non-Terrestrial Networks by Thang V. Nguyen, Hien T. T. Pham, Ngoc T. Dang

    Published 2024-12-01
    “…We develop mathematical models and derive closed-form expressions to implement the proposed algorithm and solve the optimization problem. The numerical results confirm that the JAMPC scheme helps NTN provide better energy efficiency and the ability to adapt to various channel conditions. …”
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    Article
  14. 3794

    Neural network compression for reinforcement learning tasks by Dmitry A. Ivanov, Denis A. Larionov, Oleg V. Maslennikov, Vladimir V. Voevodin

    Published 2025-03-01
    “…This work presents a systematic study on the applicability limits of using pruning and quantization to optimize neural networks in RL tasks, with a perspective of deployment in hardware to reduce power consumption and latency, while increasing throughput.…”
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  15. 3795

    Fast Low Rank and Sparse Decomposition Based on Greedy Bilateral Smoothing for Infrared Small Target Detection by Yan-Shan Zhang, Ze-Yin Li, Dong-Dong Pang, Lu-Yao Wang, Cheng-Jun Wu, Kang Duan, Jun-Ming Gao

    Published 2024-01-01
    “…Then, a optimization algorithm framework based on alternating projection is designed to achieve an accurate separation of target and background. …”
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    Article
  16. 3796

    Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents by Lida Barba, Nibaldo Rodríguez, Cecilia Montt

    Published 2014-01-01
    “…The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. …”
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  17. 3797

    IRSnet: An Implicit Residual Solver and Its Unfolding Neural Network With 0.003M Parameters for Total Variation Models by Yuanhao Gong

    Published 2025-01-01
    “…The proposed iterative method converges and converges to the optimal solution. These two facts are theoretically guaranteed and numerically confirmed, respectively. …”
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    Article
  18. 3798

    Prediction after a Horizon of Predictability: Nonpredictable Points and Partial Multistep Prediction for Chaotic Time Series by Vasilii A. Gromov, Philip S. Baranov

    Published 2023-01-01
    “…Thus, we redefine the problem of multi-step-ahead prediction as a two-objective optimization problem: on one hand, we aim to minimize the number of nonpredictable points and the average error among the predictable ones. …”
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    Article
  19. 3799

    Perception-Based H.264/AVC Video Coding for Resource-Constrained and Low-Bit-Rate Applications by Lih-Jen Kau, Chin-Kun Tseng, Ming-Xian Lee

    Published 2025-07-01
    “…By targeting regions most relevant to the human visual system, the proposed method enhances perceptual quality while optimizing resource usage, making it particularly suitable for embedded systems and bandwidth-limited communication channels. …”
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  20. 3800

    Interval-Aware Scheduling of Surveillance Drones: Exact and Heuristic Approaches by Kaito Mori, Hiroki Nishikawa, Hiroyuki Tomiyama

    Published 2025-01-01
    “…In comparison to the Greedy method, the Multi-stage method achieved an average improvement of 37.8% in total flight time, while its algorithm runtime deteriorated by a maximum of 1.26 seconds. …”
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