A Comprehensive Analysis of Supervised Learning Techniques for Electricity Theft Detection
There are many methods or algorithms applicable for detecting electricity theft. However, comparative studies on supervised learning methods for electricity theft detection are still insufficient. In this paper, comparisons based on predictive accuracy, recall, precision, AUC, and F1-score of severa...
Saved in:
Main Authors: | Farah Aqilah Bohani, Azizah Suliman, Mulyana Saripuddin, Sera Syarmila Sameon, Nur Shakirah Md Salleh, Surizal Nazeri |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Journal of Electrical and Computer Engineering |
Online Access: | http://dx.doi.org/10.1155/2021/9136206 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Electricity Theft Detection in Power Grids with Deep Learning and Random Forests
by: Shuan Li, et al.
Published: (2019-01-01) -
Revealing the differences in bicycle theft and motorcycle theft: spatial patterns and contributing factors
by: Lin Liu, et al.
Published: (2025-02-01) -
Electricity theft detection in integrated energy systems considering multi-energy loads
by: Wenlong Liao, et al.
Published: (2025-03-01) -
Theft and robbery in Chrysostom's time
by: H. F. Stander
Published: (2009-12-01) -
The ethics of theft: Reevaluating the impacts of floral larceny on plant reproductive success
by: Jin-Ru Zhong, et al.
Published: (2025-01-01)