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  1. 1861

    Insurance claims estimation and fraud detection with optimized deep learning techniques by P. Anand Kumar, S. Sountharrajan

    Published 2025-07-01
    “…The proposed work enhanced with Enhanced Hippopotamus Optimization Algorithm (EHOA) combined with a custom 12-layer CNN to optimize the hyperparameters and enhance the performance of the model. …”
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    Article
  2. 1862

    Optimal Computation Offloading Decisions Based on System Utility and Cost Balance by Bingxue Zhang, Xisheng Li, Jia You

    Published 2025-01-01
    “…Experiments conducted in a simulation based on the edge system of an industrial park verified that the cost-utility balanced optimization model achieves at least 7% reduction in the cost-utility ratio across varying user scales compared to traditional cost optimization models, while achieving over 20% reduction in optimization efficiency under different edge server scales. …”
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  3. 1863

    Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage by Aniket Basu, Hooman Oroojeni, Georgios Samakovitis, Mohammad Majid Al-Rifaie

    Published 2024-10-01
    “…The multi-drone-cell placement problem is solved using adapted Dispersive Flies Optimization alongside other meta-heuristic algorithms such as Particle Swarm Optimization and differential evolution. …”
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    Article
  4. 1864

    Optimizing Key Parameters of Ground Delay Program with Uncertain Airport Capacity by Jixin Liu, Kaijian Li, Minjia Yin, Xuehua Zhu, Ke Han

    Published 2017-01-01
    “…We also propose a joint GDP end-time-and-distance model solved with genetic algorithm. The optimization problem takes into account the GDP operational efficiency, airline and flight equity, and Air Traffic Control (ATC) risks. …”
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    Article
  5. 1865

    Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

    Published 2025-05-01
    “…In this enhanced equilibrium optimizer (EEO), the Fisher score and accuracy score of the K-Nearest Neighbors (KNN) algorithm select the attributes optimally, whereas the synthetic minority oversampling technique combined with iterative partitioning filters (SMOTE-IPF) used to provide class balancing. …”
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  6. 1866

    Robust object counting through distribution uncertainty matching and optimal transport by Sabri Boughorbel, Fethi Jarray, Rachida Zegour, Nauman Ullah Gilal, Khaled Al Thelaya, Marco Agus, Jens Schneider

    Published 2025-08-01
    “…To solve the problem, we propose a new algorithm, called Trihorn, which jointly estimates the loss function and the density map of the augmentation set. …”
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  7. 1867

    Smart energy management for revenue optimization and grid independence in an Indian RDS by T. Yuvaraj, M. Thirumalai, M. Dharmalingam, Sudhakar Babu Thanikanti, Sanjeevikumar Padmanaban

    Published 2025-04-01
    “…The framework employs the hunter-prey optimization algorithm (HPOA) to enhance appliance scheduling, renewable energy integration (PV, WT, EV, BESS), and dynamic tariff management while addressing uncertainties in electric vehicle (EV) usage and renewable distributed generation (RDG) output. …”
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    Article
  8. 1868

    Optimization Scheduling of Multi-Regional Systems Considering Secondary Frequency Drop by Xiaodong Yang, Xiaotong Hua, Lun Cheng, Tao Wang, Yujing Su

    Published 2025-07-01
    “…The column and constraint generation algorithm is employed to solve this two-stage optimization problem. …”
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    Article
  9. 1869

    Collaborative optimal operation control of HVAC systems based on multi-agent by Chen Fu, Kaipeng Chen, Yan Xu, Dongyue Ming, Ruiwen Ye, Yingjun Wu, Lixia Sun

    Published 2025-07-01
    “…As a consequence, the computing efficiency of optimization algorithms is relatively low, posing challenges for real-time optimal operation control. …”
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    Article
  10. 1870

    Bayesian optimization of underground railway tunnels using a surrogate model by Hassan Liravi, Hoang-Giang Bui, Sakdirat Kaewunruen, Aires Colaço, Jelena Ninić

    Published 2025-01-01
    “…The results demonstrate that the proposed optimization framework, which combines the Bayesian optimization algorithm with surrogate models, effectively explores trade-offs among multiple design parameters. …”
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    Article
  11. 1871
  12. 1872

    Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

    Published 2025-05-01
    “…This paper seeks to elucidate the efficacy of deep learning models in medical diagnostics by employing concepts and strategies derived from biological system ontologies, such as genetic algorithms, particle swarm optimization, ant colony optimization, artificial immune systems, and swarm intelligence. …”
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    Article
  13. 1873

    Optimization of Shift Strategy Based on Vehicle Mass and Road Gradient Estimation by Huijun Yue, Haobo Jing, Zhenkun Dai, Jinyu Lin, Zihan Ma, Changtong Zhao, Pan Zhang

    Published 2024-11-01
    “…According to the estimation results, the existing shift strategy is optimized, and the software-in-the-loop simulation of the transmission controller is carried out to verify the function of the control algorithm software. …”
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    Article
  14. 1874

    Conveyor X-Ray Tomosynthesis Imaging With Optimized Structured Sequential Illumination by Xu Ma, Dong Wang, Angela Cuadros, Tianyi Mao, Qile Zhao, Gonzalo R. Arce, Tingfa Xu

    Published 2020-01-01
    “…Subsequently, a genetic algorithm is developed to optimize the exposure sequence of X-ray sources, and mask patterns, and during the dynamic measurement process. …”
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  15. 1875

    Low Complexity Optimized AOR Method for Massive MIMO Signal Detection by Muhammad Nauman Irshad, Muhamamd Muzamil Aslam, Rardchawadee Silapunt

    Published 2025-01-01
    “…To determine these parameters systematically, we incorporate an innovative approach using the Nelder-Mead Simplex optimization algorithm. This heuristic optimization technique allows us to find the optimal acceleration and relaxation parameters, thereby achieving superior detection accuracy with faster convergence for challenging system configurations. …”
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  16. 1876

    Numerical simulation and optimization for dynamic responses of floating hoses in CALM system by Ke HU, Chen AN, Aixia ZHANG, Kexin CHEN, Xianjing BAI

    Published 2024-06-01
    “…Subsequently, the genetic algorithm was leveraged to facilitate the optimization of floating hose configurations, leading to a multi-objective optimized design aimed at minimizing effective tension and curvature. …”
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    Article
  17. 1877

    Dynamic Optimization of Recurrent Networks for Wind Speed Prediction on Edge Devices by Laeeq Aslam, Runmin Zou, Ebrahim Shahzad Awan, Sayyed Shahid Hussain, Muhammad Asim, Samia Allaoua Chelloug, Mohammed A. ELAffendi

    Published 2025-01-01
    “…Server-dependent machine learning models, commonly deployed in wind farms, prove infeasible for domestic systems due to high costs and energy demands. While edge computing offers a viable alternative, current WSP methods prioritize hyperparameter optimization without constraining model size (MS), resulting in memory-intensive architectures incompatible with resource-limited devices. …”
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    Article
  18. 1878
  19. 1879

    The Optimization of Stand Structure Can Significantly Alleviate the Flammability of Forest Ecosystems by Yan Zhang, Xiangwen Deng, Xiaoyong He, Xiaolong Zhang, Zhihong Huang, Liang Chen, Shuai Ouyang, Wenhua Xiang

    Published 2025-05-01
    “…Rutaceae and Cucurbitaceae plants exhibited relatively high flammability, while Arecaceae plants demonstrated characteristics of low flammability. …”
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    Article
  20. 1880

    Entire aerial-aquatic trajectory modeling and optimization for trans-medium vehicles by Teng Long, Nianhui Ye, Baoshou Zhang, Jingliang Sun, Renhe Shi

    Published 2025-07-01
    “…Simultaneously, several constraints, i.e., the max impact load, trajectory height, etc., are involved in the optimization problem. Rather than directly optimizing by a heuristic algorithm, a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem. …”
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