Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory
Anomaly detection; Brain; Errors; Forecasting; Gradient methods; Mean square error; Optimization; Statistics; Stochastic models; Stochastic systems; Anomaly detection; Electricity load; Electricity theft; Load predictions; Mean absolute error; Mean squared error; Optimizers; Point detection; Power p...
Saved in:
Main Authors: | Salleh N.S.M., Saripuddin M., Suliman A., Jorgensen B.N. |
---|---|
Other Authors: | 54946009300 |
Format: | Conference Paper |
Published: |
Institute of Electrical and Electronics Engineers Inc.
2023
|
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Experiment on Electricity Consumption Prediction using Long Short-Term Memory Architecture on Residential Electrical Consumer
by: Md Salleh N.S., et al.
Published: (2023) -
A Systematic Literature Review of Electricity Load Forecasting using Long Short-Term Memory
by: Salleh N.S.M., et al.
Published: (2023) -
Comparison of Electricity Usage Forecasting Model Evaluation Based on Historical Load Dataset Duration Using Long Short-Term Memory Architecture
by: Salleh N.S.M., et al.
Published: (2023) -
Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer
by: Salleh N.S.M., et al.
Published: (2023) -
Long short-term memory autoencoder-based anomaly detection system for electric motors
by: Sharrar, Labib
Published: (2022)