# Electricity Theft Detection Techniques

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/electricity-theft-detection-techniques-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 53,438 |
| Description | This cluster of papers focuses on the detection and prevention of electricity theft in smart grids, particularly through the use of advanced metering infrastructure, machine learning, deep learning, and anomaly detection techniques. The research explores methods such as support vector machines, decision trees, convolutional neural networks, and feature engineering to address non-technical losses and improve the security of electricity distribution systems. |
| Domain | Physical Sciences |
| Field | Engineering |
| OpenAlex ID | https://openalex.org/T13429 |
| Works | 14,549 |

## Topic researchers

Showing 12 of 20.

- [Francisco Herrera](https://scholariq.org/researchers/francisco-herrera/)
- [Xuemin Shen](https://scholariq.org/researchers/xuemin-shen/)
- [O. Bouhali](https://scholariq.org/researchers/o-bouhali/)
- [MengChu Zhou](https://scholariq.org/researchers/mengchu-zhou/)
- [Xin Yao](https://scholariq.org/researchers/xin-yao/)
- [Victor C. M. Leung](https://scholariq.org/researchers/victor-c-m-leung/)
- [C. L. Philip Chen](https://scholariq.org/researchers/c-l-philip-chen/)
- [Neeraj Kumar](https://scholariq.org/researchers/neeraj-kumar/)
- [Kim‐Kwang Raymond Choo](https://scholariq.org/researchers/kim-kwang-raymond-choo/)
- [Athanasios V. Vasilakos](https://scholariq.org/researchers/athanasios-v-vasilakos/)
- [Nitesh V. Chawla](https://scholariq.org/researchers/nitesh-v-chawla/)
- [Taghi M. Khoshgoftaar](https://scholariq.org/researchers/taghi-m-khoshgoftaar/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.