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  1. 361

    Optimized 3D Deployment of UAV-Mounted Cloudlets to Support Latency-Sensitive Services in IoT Networks by Islambouli, Rania

    Published 2019
    “…We formulate the problem as a mixed integer program, and propose an efficient meta-heuristic solution based on the ions motion optimization algorithm. …”
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    article
  2. 362

    Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh (22565837)

    Published 2025
    “…We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”
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  5. 365

    Wrapper-Based Feature Selection to Classify Flatfoot Disease by Casas-Ordaz, Angel

    Published 2024
    “…This task is considered from an optimization perspective, and the optimal subset is chosen using metaheuristic algorithms. …”
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  6. 366

    Wrapper-Based Feature Selection to Classify Flatfoot Disease by Casas-Ordaz, Angel

    Published 2024
    “…This task is considered from an optimization perspective, and the optimal subset is chosen using metaheuristic algorithms. …”
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  7. 367

    AI-driven nonlinear optimization for knowledge extraction and pattern analysis in IoT-enabled data mining systems by Alimjon, Dadamuxamedov

    Published 2025
    “…In this paper, systematic exploration of the application of AI-based nonlinear optimization to elicit knowledge and pattern study in the IoT-enabled data mining takes place. …”
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    article
  8. 368

    Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

    Published 2024
    “…The results demonstrate that the suggested RF-ANN-based technique can predict the optimal composite design with high accuracy (precision, recall, and f1-score for test and train dataset were 1). …”
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  10. 370

    Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach by Mohammad Taghi Dabiri (16904658)

    Published 2023
    “…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …”
  11. 371

    A cluster-based model for QoS-OLSR protocol by Otrok, Hadi

    Published 2017
    “…Therefore, we propose a novel clustering algorithm and a relay node selection based on different combinations of metrics, such as connectivity, residual energy, and bandwidth. …”
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  12. 372

    Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier by JAIN, SWETA

    Published 2023
    “…The hyper parameters are optimized with DM optimization algorithm which improves the accuracy of classifier. …”
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  13. 373

    Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

    Published 2023
    “…The complex gas hydrate prevention unit is simulated using the MLPNN model trained by 20 different optimization algorithms. This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. …”
  14. 374

    Hybridizing rule-based power system stabilizers with geneticalgorithms by Abido, M.A.

    Published 1999
    “…The proposed approach uses genetic algorithms (GA) to search for optimal settings of rule-based power system stabilizer (RBPSS) parameters. …”
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    article
  15. 375

    Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

    Published 2021
    “…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. We show how our algorithm supports the definition of a budget for alignment computation and also augment it with strategies for meta-heuristic optimization and pruning of the search space. …”
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  16. 376

    Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by Reza Jafari (3494018)

    Published 2025
    “…In addition to the deployment without requiring an explicit model of the plant, the simulation results demonstrate that the proposed solution modifies vehicle dynamics and maneuverability in most cases compared to the model-based conventional controller. Furthermore, the reduction in sideslip angle, excellent traction through minimizing tire slip ratio, avoiding oversteering and understeering, and maintaining an acceptable range of energy optimization are demonstrated for DRL controllers, especially for the TD3 and CL TD3 algorithms.…”
  17. 377

    Artificial intelligence–empowered digital twins for simulation-driven security, privacy, and resiliency optimization in 6G networks by Senthilkumar, P.

    Published 2025
    “…In this survey, the Digital Twin frameworks based on AI are thoroughly revised in terms of improving the security, privacy, and resiliency of 6G networks, with a specific focus on Digital Twin modelling and prediction algorithms, such as, graph-based, temporal, and representation learning algorithms. …”
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  18. 378

    Coordinated design of robust excitation and TCSC-based damping controllers by Abido, M.A.

    Published 2003
    “…The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. …”
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    article
  19. 379

    A combinatorial auction‐based approach for ridesharing in a student transportation system by Chefi Triki (14158860)

    Published 2023
    “…A hybrid heuristic-based optimization framework, that takes advantage of meta-heuristic algorithms to improve an initial solution, is also developed to solve large-sized instances of the problem. …”
  20. 380

    Improving multilayer perceptron neural network using two enhanced moth-flame optimizers to forecast iron ore prices by Ahmed, Basem

    Published 2024
    “…In this article, we propose two new optimization algorithms based on the moth-flame optimization algorithm (MFO), which mimics moths’ special navigation methods at night. …”
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