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  1. 1621

    Bilevel Optimization for ISAC Systems with Proactive Eavesdropping Capabilities by Tingyue Xue, Wenhao Lu, Mianyi Zhang, Yinghui He, Yunlong Cai, Guanding Yu

    Published 2025-07-01
    “…With the help of the proposed algorithm, we obtain the optimal solution of the analog transmit beamforming matrix and the digital beamforming vector. …”
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  2. 1622

    Signal Timing Optimization Model for Intersections in Traffic Incidents by Jiawen Wang, Jiayu Hang, Xizhao Zhou

    Published 2020-01-01
    “…To satisfy the conditions for efficiently identifying feasible solutions in a short time, a heuristic algorithm (simulated annealing algorithm) is employed to solve the model. …”
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  3. 1623

    Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

    Published 2025-02-01
    “…With the continuous research by domestic scholars, YOLO algorithm is also continuously iteratively optimized, and its ability to detect the objects of different sizes and shapes is significantly improved, which can adapt to the maturity degree, size and occlusion of fruits, and improve the detection performance in complex environments.…”
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  4. 1624

    Lightweight Apple Leaf Disease Detection Algorithm Based on Improved YOLOv8 by LUO Youlu, PAN Yonghao, XIA Shunxing, TAO Youzhi

    Published 2024-09-01
    “…To reduce the incidence of apple diseases and increase fruit yield, developing efficient and fast apple leaf disease detection technology is of great significance. An improved YOLOv8 algorithm was proposed to identify the leaf diseases that occurred during the growth of apples.…”
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    Article
  5. 1625

    Optimal Poisson Cognitive System with Markov Learning Model by A. A. Solodov

    Published 2021-12-01
    “…Thus, the following assumptions are accepted in the work, apparently corresponding to the behavior of the system assuming human reactions, i.e. the cognitive system.The images analyzed by the system arise at random moments of time, while the duration of time between neighboring appearances of images is distributed exponentially.The system analyzes the resulting images and makes a decision about the presence or absence of an image at its input in accordance with the optimal Neуman-Pearson algorithm that maximizes the probability of correct identification of the image with a fixed probability of false identification.The system is trainable in the sense that decisions about the presence or absence of an image are made sequentially on a set of identical situations, and the probability of making a decision depends on the previous decision of the system.The new results of the study are analytical expressions for the probabilities of the system staying in each of the possible states, depending on the number of steps of the learning process and the intensities of useful and interfering stimuli at the input of the system. …”
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  6. 1626

    An Incentive Dynamic Programming Method for the Optimization of Scholarship Assignment by Di Huang, Yu Gu, Hans Wang, Zhiyuan Liu, Jun Chen

    Published 2018-01-01
    “…The objective is to find the optimal scholarship assignment scheme with the highest equity while accounting for both the practical constraints and the equity requirement. …”
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    Article
  7. 1627

    Optimizing Medical IoT Disaster Management with Data Compression by Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

    Published 2024-02-01
    “…To tackle this issue, we introduce "Beyond Orion," a novel lossless compression method designed to optimize data compression in IoT systems. The algorithm employs advanced techniques such as Lempel Ziv-Welch and Huffman encoding, while also integrating strategies like pipelining, parallelism, and serialization for greater efficiency and lower resource usage. …”
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    Article
  8. 1628

    Optimizing the Finishing Treatment of Potato Harvester Transmission Shafts by A. V. Nemenko, M. M. Nikitin

    Published 2024-03-01
    “…This function is designed to maximize potato yield while monitoring concentrated defects. (Materials and methods) The implementation of the method requires equipment capable of being controlled through a technical vision channel. …”
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  9. 1629

    Layout Optimization of Campus Bike-Sharing Parking Spots by Tangyi Guo, Jie Yang, Liu He, Kun Tang

    Published 2020-01-01
    “…Thus, alternative parking spots are proposed based on the layout principle of parking spots for bicycles. An optimization model of the layout of campus bike-sharing parking spots with travel time and construction cost as the optimization goal is established, and the branch and bound algorithm is used to solve the model. …”
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    Article
  10. 1630

    Superposition Methods for Topology Optimization for Non-Concurrent Loads by Daniel Miler, Matija Hoić

    Published 2025-01-01
    “…Problems with non-concurrent loads with variable load directions are often encountered in engineering. While dynamic topology optimization more realistically solves such problems, it is also much more computationally expensive and requires complex mathematical formulations and solvers. …”
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  11. 1631
  12. 1632

    Optimization of PID Controllers Using Groupers and Moray Eels Optimization with Dual-Stream Multi-Dependency Graph Neural Networks for Enhanced Dynamic Performance by Vaishali H. Kamble, Manisha Dale, R. B. Dhumale, Aziz Nanthaamornphong

    Published 2025-04-01
    “…This study presents a novel control strategy that integrates the Groupers and Moray Eels Optimization (GMEO) algorithm with a Dual-Stream Multi-Dependency Graph Neural Network (DMGNN) to optimize PID controller parameters. …”
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    Article
  13. 1633

    METHOD OF QUALIFICATION ESTIMATION AND OPTIMIZATION OF PROFESSIONAL TEAMS OF PROGRAMMERS by A. A. Prihozhy, A. M. Zhdanouski

    Published 2018-08-01
    “…The problem of building and optimizing the teams of programmers taking into account the qualification and the level of skills in programming technologies and tools is considered. …”
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  14. 1634

    Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

    Published 2025-01-01
    “…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. While optimized PID serves as a baseline, hybrid controllers consistently achieve faster settling times and improved robustness under most nonlinear operating conditions. …”
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  15. 1635

    Precision irrigation with AI-driven optimization of plant electrophysiology by Yiting Chen, Devon Scott, Hieu Trung Tran, Yan Sum Shirley Yip, Soomin Shin, Woo Soo Kim

    Published 2025-12-01
    “…By optimizing water consumption using the AI algorithm, our approach can achieve at least a 10 % reduction in water use while maintaining optimal water conditions for crops. …”
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  16. 1636

    Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization by Perne Mallikarjun, Sundar Rajan Giri Thulasiraman, Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri

    Published 2025-03-01
    “…Three distinct wireless EV charging load profiles are considered to evaluate the performance of the proposed optimization technique. Simulation results demonstrate that the IHHO algorithm achieves significant cost reductions and improves energy utilization efficiency compared to other state-of-the-art optimization algorithms such as Improved Quantum Particle Swarm Optimization (IQPSO), Honeybee Mating Optimization (HBMO), and Enhanced Exploratory Whale Optimization Algorithm (EEWOA). …”
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  17. 1637
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  20. 1640

    Optimization of non-smooth functions via differentiable surrogates. by Shikun Chen, Zebin Huang, Wenlong Zheng

    Published 2025-01-01
    “…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …”
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