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Multi-site Information Synchronization Scheme Based on Wavelet Transform to Detect Signal Singularity
Published 2024-12-01Get full text
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543
Assessing the risk of traffic accidents in lisbon using a gradient boosting algorithm with a hybrid classification/regression approach
Published 2025-07-01“…This research presents a novel two-stage gradient-boosting predictive model, using tree-based learning algorithms to analyze traffic accidents requiring firefighter intervention in Lisbon, Portugal. …”
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Power Communication Network Recovery from Large-Scale Failures Based on Reinforcement Learning
Published 2020-06-01Get full text
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546
NSGA-II-based load resource management for frequency and voltage support
Published 2025-04-01Get full text
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547
Penerapan Feature Engineering dan Hyperparameter Tuning untuk Meningkatkan Akurasi Model Random Forest pada Klasifikasi Risiko Kredit
Published 2025-04-01“…This research aims to improve the accuracy of the Random Forest algorithm classification model by implementing parameter tuning and feature engineering. …”
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Rendering algorithm for 3D model of goods in power warehouse based on linear interpolation and 2D texture mapping
Published 2025-08-01“…Deployment at a State Grid hub warehouse elevated sorting throughput by 40% and slashed manual verification workload by 65%. …”
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Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data
Published 2025-06-01“…In this study, we propose a new approach for constructing real-time icing grid fields using 1339 online terminal monitoring datasets provided by the China Southern Power Grid Research Institute Co., Ltd. …”
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Artificial Intelligence in Virtual Screening: Transforming Drug Research and Discovery—A Review
Published 2025-01-01Get full text
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Solar FaultNet: Advanced Fault Detection and Classification in Solar PV Systems Using SwinProba‐GeNet and BaBa Optimizer Models
Published 2025-07-01“…Besides, the proposed model outperforms conventional machine‐learning algorithms and state‐of‐the‐art deep‐ learning models for better performance by yielding higher accuracy, precision, recall, F1‐score, and low error rate on various fault types such as PV array faults, inverter faults, grid synchronization faults, and environmental faults. …”
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