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  1. 3881

    Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

    Published 2025-06-01
    “…Regression and classification models were developed using gradient boosting, random forest, and CatBoost algorithms. …”
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    Article
  2. 3882
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    Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine by Hojin Moon, Lauren Tran, Andrew Lee, Taeksoo Kwon, Minho Lee

    Published 2024-10-01
    “…Methods: To accomplish our research goal, we implement ensemble learning algorithms, bagging with regularized Cox regression models and nonparametric tree-based models via Random Survival Forests. …”
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  4. 3884

    Weight optimization of steel lattice transmission towers based on Differential Evolution and machine learning classification technique by Tran-Hieu Nguyen, Anh-Tuan Vu

    Published 2021-12-01
    “…A classification model based on the Adaptive Boosting algorithm is developed in order to eliminate unpromising candidates during the optimization process. …”
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    Article
  5. 3885

    Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting by Farideh Sobhanifard

    Published 2025-07-01
    “…Thus, in this paper, a hybrid innovative Gaussian Particle Swarm Optimization and fuzzy logic model is proposed to optimize the Bayesian Neural Networks in weight and structure. …”
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    Article
  6. 3886
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    Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era by Weigang Jin, Peihua Wang, Jiaxin Yuan

    Published 2024-11-01
    “…For each method, this review presents its mathematical models and solution algorithms. This review highlights the significance of TVPPs in enhancing power system flexibility, improving renewable energy integration, and providing ancillary services. …”
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    Article
  9. 3889
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  11. 3891

    Federated learning framework for IoT intrusion detection using tab transformer and nature-inspired hyperparameter optimization by Mohamed Abd Elaziz, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Ibrahim A. Fares, Abdelghani Dahou, Mansour Shrahili

    Published 2025-05-01
    “…To address these challenges, this paper introduces a novel trust-centric FL framework based on the tab transformer (TTF) model for IDS. We enhance the Tab model through an optimization process, utilizing a hyperparameter tuning algorithm inspired by the nature-based electric eel foraging optimization (EEFO) algorithm. …”
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  12. 3892

    DAMAGE IDENTIFICATION METHOD BASED KRIGING MODEL by MA JingJing, YIN Hong, PENG ZhenRui, DONG KangLi

    Published 2020-01-01
    “…To improve damage identification efficiency,a damage identification method based on Kriging model was proposed. …”
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  13. 3893

    Optimization of load-bearing parameters for anisotropic nodes and prefabricated wall panels in prefabricated shear wall structures. by Jun Zhao, Libo Wang, Tengye Ma

    Published 2025-01-01
    “…Therefore, the study improves the quality information model for prefabricated nodes and the dragonfly algorithm by introducing principal component dimensionality reduction methods and multiple strategies through data modeling. …”
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    Article
  14. 3894

    Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu, Baijuan Wang

    Published 2025-01-01
    “…Additionally, Shape Weights and Scale Adjustment Factors are introduced to optimize the loss function. The experimental results show that compared with the original YOLOv10, the model generated by the improved algorithm improves the accuracy by 5.88 percentage points, the recall rate by 6.67 percentage points, the balance score by 6.27 percentage points, the mAP value by 4.26 percentage points, the bounding box loss by 18.75%, the classification loss by 27.27%, and the feature point loss by 8%. …”
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  15. 3895

    ENHANCING DISEASE DETECTION PREDICTION ACCURACY OF GRAPE LEAVES USING VGG16 MODEL AND INCEPTION V3 MODEL by Deepshikha Yadav, Archana Balyan, Suman Mann, Aayush Ranga

    Published 2025-03-01
    “…The study aims to guide the selection of an optimal algorithm for grape leaf and disease detection, contributing to the overall enhancement of grape cultivation practices. …”
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    Article
  16. 3896

    Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

    Published 2022-01-01
    “…Machine learning of median grain size from conventional logging data was systematically carried out through conventional logging sensitivity curve optimization, algorithm modeling, network parameter optimization, median grain size prediction, and validation, and the relative error in its quantitative prediction met application requirements. …”
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    Application of GA in Furniture Modeling Style Design by Heng Yu, Chunjing Liu

    Published 2022-01-01
    “…In this paper, an interactive innovation evolution system based on evolutionary algorithm is proposed. Taking full advantage of the evolution function of genetic algorithm and the modeling advantages of ACIS platform, a prototype innovation evolution system is developed based on ACIS/hoops platform with the genetic algorithm based on tree structure as the innovation support, which can help designers complete the innovation modeling design. …”
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    Article
  20. 3900

    From Baseline to Best Practice: An Advanced Feature Selection, Feature Resampling and Grid Search Techniques to Improve Injury Severity Prediction by Soukaina EL Ferouali, Zouhair Elamrani Abou Elassad, Sara Qassimi, Abdelmounaîm Abdali

    Published 2025-12-01
    “…Our findings provide insight into the requirement for accurate forecasting models in optimization and balanced approaches to enhancing traffic safety. …”
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    Article