Power Theft Detection Using Deep Neural Networks
Author:
Affiliation:
1. Department of Computer Science and Engineering, Chandigarh College of Engineering and Technology, Chandigarh, India
2. Department of Computer Science and Engineering, Punjab Engineering College (Deemed to be University), Chandigarh, India
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Energy Engineering and Power Technology
Link
https://www.tandfonline.com/doi/pdf/10.1080/15325008.2021.1970055
Reference50 articles.
1. “World loses $89.3 billion to electricity theft annually, $58.7 billion in emerging markets – Utility industry looks toward smart grid infrastructure to combat losses”, Northeast LLC, Washington, DC. [Online]. Available: https//www.prnewswire.com/news-releases/world-loses-893-billion-to-electricity-theft-annually-587-billion-in-emerging-markets-300006515.html. Accessed: Jun. 20, 2019.
2. Wide and Deep Convolutional Neural Networks for Electricity-Theft Detection to Secure Smart Grids
3. Smart Grids: A Cyber–Physical Systems Perspective
4. Development of ARM processor based electricity theft control system using GSM network
5. Decision Tree and SVM-Based Data Analytics for Theft Detection in Smart Grid
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