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Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine
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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4264
An Optimized Spline-Based Registration of a 3D CT to a Set of C-Arm Images
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4265
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4266
Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era
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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Federated learning framework for IoT intrusion detection using tab transformer and nature-inspired hyperparameter optimization
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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4270
DAMAGE IDENTIFICATION METHOD BASED KRIGING MODEL
Published 2020-01-01“…To improve damage identification efficiency,a damage identification method based on Kriging model was proposed. …”
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4271
Optimization of load-bearing parameters for anisotropic nodes and prefabricated wall panels in prefabricated shear wall structures.
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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4272
Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework
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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4273
ENHANCING DISEASE DETECTION PREDICTION ACCURACY OF GRAPE LEAVES USING VGG16 MODEL AND INCEPTION V3 MODEL
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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4274
Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm
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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4275
Enhancing Upper Limb Exoskeletons Using Sensor-Based Deep Learning Torque Prediction and PID Control
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4276
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From Baseline to Best Practice: An Advanced Feature Selection, Feature Resampling and Grid Search Techniques to Improve Injury Severity Prediction
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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4278
Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure
Published 2024-09-01“…It was proven through the experimental results that the proposed distance measure Weighted Euclidean distance had the advantage over improving the work of the HFCM algorithm through the criterion (Obj_Fun, Iteration, Min_optimization, good fit clustering and overlap) when (c = 2,3) and according to the simulation results, c = 2 was chosen to form groups for the real data, which contributed to determine the best objective function (23.93, 22.44, 18.83) at degrees of fuzzing (1.2, 2, 2.8), while according to the degree of fuzzing (m = 3.6), the objective function for Euclidean Distance (ED) was the lowest, but the criteria were (Iter. = 2, Min_optimization = 0 and ) which confirms that (WED) is the best.…”
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Multiperiod Location–Allocation Optimization of Construction Logistics Centers for Large-Scale Projects in Complex Environmental Regions
Published 2025-03-01“…We have designed an NSGA-II based on endocrine hormone regulation (EHR-NSGA-II) to solve the model. Finally, a large-scale railroad construction project in complex environmental regions is used as an example to prove the effectiveness of the model and algorithm. …”
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Optimal State Estimation in Underwater Vehicle Discrete-Continuous Measurements via Augmented Hybrid Kalman Filter
Published 2025-05-01“…State-vector augmentation is proposed to improve the estimation convergence. The authors present numerical modeling results demonstrating the algorithm’s efficiency on the example of motion parameter estimation for the autonomous underwater vehicle. …”
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