Industrial development with the growth, strengthening, stability, technical advancement,
reliability, selection, and dynamic response of the power system is essential. Governments …

Abstract Gradient Boosted Decision Trees (GBDT's) are a powerful tool for classification and
regression tasks in Big Data. Researchers should be familiar with the strengths and …

For the smart grid energy theft identification, this letter introduces a gradient boosting theft
detector (GBTD) based on the three latest gradient boosting classifiers (GBCs): 1) extreme …

The digital landscape of the Internet of Energy (IoE) is on the brink of a revolutionary
transformation with the integration of edge Artificial Intelligence (AI). This comprehensive …

This paper presents a novel supervised machine learning-based electric theft detection
approach using the feature engineered-CatBoost algorithm in conjunction with the …

Advanced metering infrastructure allows the two-way sharing of information between smart
meters and utilities. However, it makes smart grids more vulnerable to cyber-security threats …

Electricity theft has been a growing concern for the smart grid. It can be defined as follows:
illegal customers use energy from electric utilities without a contract or manipulate their …

The pace of society development is faster than ever before, and the smart city paradigm has
also emerged, which aims to enable citizens to live in more sustainable cities that guarantee …

In smart grids, homes are equipped with smart meters (SMs) to monitor electricity
consumption and report fine-grained readings to electric utility companies for billing and …

The big data sources in smart grid (SG) enable utilities to monitor, control, and manage the
energy system effectively, which is also promising to advance the efficiency, reliability, and …