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  2. 2202

    Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

    Published 2024-01-01
    “…For resource allocation, the framework employs the Time-aware modified best fit decreasing (T-MBFD) algorithm, which adapts to fluctuating workloads. Key input parameters for T-MBFD include available resources, job size, and time constraints, while output parameters focus on optimized resource distribution and minimizing wastage. …”
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  3. 2203

    Optimizing Hybrid Renewable Energy Systems for Enhanced Sustainability and Efficiency in Rural Communities by Bartolomeo Cosenza, Gabriele Pannocchia, Marco Vaccari

    Published 2025-07-01
    “…The developed algorithm determines optimal operating setpoints for each generator, carefully balancing system constraints while ensuring uninterrupted power delivery to meet load demands. …”
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  4. 2204

    Modeling and Optimization of Beam Pumping System Based on Intelligent Computing for Energy Saving by Xiaohua Gu, Taifu Li, Zhiqiang Liao, Liping Yang, Ling Nie

    Published 2014-01-01
    “…It firstly employs the general regression neural network (GRNN) algorithm to obtain the best model of the beam pumping system, and secondly searches the optimal operation parameters with improved strength Pareto evolutionary algorithm (SPEA2). …”
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  5. 2205

    Optimization of signal control at ramp adjacent intersections based on A2C by SONG Tailong, GUO Mingyang, CHEN Yifan, HE Yulong

    Published 2024-03-01
    “…This study utilizes deep reinforcement learning algorithms for traffic signal control optimization at exit ramps associated with intersection crossings. …”
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  6. 2206
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    A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling by Pujie Han, Wentao Hu, Zhengjun Zhai, Min Huang

    Published 2024-11-01
    “…This paper proposes a model-based optimization method for ARINC 653 multicore partition scheduling. …”
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  8. 2208

    An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

    Published 2025-05-01
    “…The proposed method is called the Dimensional Archimedes Optimization Algorithm (DAOA). DAOA is based on the Archimedes Optimization Algorithm (AOA) and Dimensional Learning Strategy (DLS). …”
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    Applications of Recent Metaheuristic Algorithms for Loss Reduction in Distribution Power Systems considering Maximum Penetration of Photovoltaic Units by Le Duy Luan Nguyen, Phuc Khai Nguyen, Viet Cuong Vo, Ngoc Dieu Vo, Thang Trung Nguyen, Tan Minh Phan

    Published 2023-01-01
    “…Photovoltaic units (PVUs) are placed optimally by implementing the Coot optimization algorithm (COOA), the archimedes optimization algorithm (AOA), the transient search optimization algorithm (TSOA), the crystal structure algorithm (CrSA), the war strategy optimization algorithm (WSA), and the average and subtraction-based optimizer (ASBO). …”
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  11. 2211

    Accuracy–Efficiency Trade-Off: Optimizing YOLOv8 for Structural Crack Detection by Jiahui Zhang, Zoia Vladimirovna Beliaeva, Yue Huang

    Published 2025-06-01
    “…To address the accuracy–efficiency trade-off faced by deep learning models in structural crack detection, this paper proposes an optimized version of the YOLOv8 model. YOLO (You Only Look Once) is a real-time object detection algorithm known for its high speed and decent accuracy. …”
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  12. 2212

    A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction by Raghunath Dey, Jayashree Piri, Biswaranjan Acharya, Pragyan Paramita Das, Vassilis C. Gerogiannis, Andreas Kanavos

    Published 2025-03-01
    “…To address this, effective feature selection is essential but remains an NP-hard challenge best tackled with heuristic algorithms. This study introduces a binary, multi-objective starfish optimizer for optimal feature selection, balancing feature reduction and classification performance. …”
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    Networked Sensor-Based Adaptive Traffic Signal Control for Dynamic Flow Optimization by Xinhai Wang, Wenhua Shao

    Published 2025-06-01
    “…This method integrates the Webster algorithm with a proportional–integral–derivative (PID) controller, whose parameters are optimized using a genetic algorithm, thereby facilitating scientifically informed traffic signal timing strategies for enhanced traffic regulation. …”
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  15. 2215

    Optimizing Masks and Random Screening Test Usage within K-12 Schools by Yiwei Zhang, Maria E. Mayorga, Julie S. Ivy, Julie L. Swann

    Published 2025-01-01
    “…Many studies discussed the effectiveness of various interventions, while few focused on optimizing such interventions. …”
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    K-Means Based Bee Colony Optimization for Clustering in Heterogeneous Sensor Network by Prince Modey, Gaddafi Abdul-Salaam, Emmanuel Freeman, Patrick Acheampong, William Leslie Brown-Acquaye, Israel Edem Agbehadji, Richard C. Millham

    Published 2024-11-01
    “…While the traditional bee colony optimization technique has been widely used as a clustering technique in WSN, it mostly suffers from energy efficiency and network performance. …”
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  18. 2218

    LEVELS OF PATIENTS EXPOSURE AND A POTENTIAL FOR OPTIMIZATION OF THE PET DIAGNOSTICS IN THE RUSSIAN FEDERATION by L. A. Chipiga, I. A. Zvonova, D. V. Ryzhkova, M. A. Menkov, М. B. Dolgushin

    Published 2018-01-01
    “…Low dose computed tomography protocols, justification of diagnostic and multiphase computed tomography protocols, application of tube current modulation system and modern reconstruction algorithms, education and training of the staff in the field of radiation protection should be used for optimization of radiation protection of patient.…”
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    Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

    Published 2023-09-01
    “…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
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