Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer
Brain; Errors; Forecasting; Learning algorithms; Mean square error; Memory architecture; Network architecture; Smart meters; Time series; Demand-side; Electricity load; Error values; Load predictions; Machine learning algorithms; Mean absolute error; Mean squared error; Prediction errors; Regression...
Saved in:
Main Authors: | Salleh N.S.M., Suliman A., J�rgensen B.N. |
---|---|
Other Authors: | 54946009300 |
Format: | Conference Paper |
Published: |
Springer Science and Business Media Deutschland GmbH
2023
|
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
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) -
A Systematic Literature Review of Electricity Load Forecasting using Long Short-Term Memory
by: Salleh N.S.M., et al.
Published: (2023) -
Experiment on Electricity Consumption Prediction using Long Short-Term Memory Architecture on Residential Electrical Consumer
by: Md Salleh N.S., et al.
Published: (2023) -
Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory
by: Salleh N.S.M., et al.
Published: (2023) -
Development of Gas Flow Characteristic Prediction for Industrial Flow Meter using Long Short-Term Memory (LSTM)
by: Mustafa, Mohd Faizal, et al.
Published: (2022)