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An Improved YOLOv8-XGBoost load rapid identification method based on multi-feature fusion

Existing non-intrusive load monitoring (NILM) approaches face challenges including limited identification accuracy, computationally intensive architectures, and constrained generalization performance. To address these issues, this paper proposes an Improved YOLOv8-XGBoost rapid load identification m...

Whakaahuatanga katoa

I tiakina i:
Ngā kaituhi matua: JianYuan Wang, Long Cheng
Hōputu: Artigo
Reo:Inglês
I whakaputaina: Elsevier 2025-05-01
Rangatū:International Journal of Electrical Power & Energy Systems
Ngā marau:
Non-Intrusive Load Identification
MTF Encoding
Feature Fusion
YOLOv8 Neural Network
XGBoost Algorithm
Urunga tuihono:http://www.sciencedirect.com/science/article/pii/S0142061525001243
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