An AI explained data-driven framework for electricity theft detection with optimized and active machine learning

Nadeem Javaid

doi:10.1016/j.apenergy.2025.126632

An AI explained data-driven framework for electricity theft detection with optimized and active machine learning

2025-08-22

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DOI：10.1016/j.apenergy.2025.126632

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Abstract

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• LoRAS balancing technique is employed to balance the dataset. • We proposed two novel deep models, ASGD and CSGD, for classification. • 10-FCV is used to validate the results of the proposed models. • To understand feature contributions, we use explainable AI techniques, SHAP and LIME.

Keywords:

LoRAS balancing

ASGD

CSGD

10-FCV

SHAP

LIME

An AI explained data-driven framework for electricity theft detection with optimized and active machine learning

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