TELKOMNIKA Telecommunication, Computing, Electronics and Control
Feature engineering and long short-term memory for energy use of appliances prediction

Dublin Core

Title

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Feature engineering and long short-term memory for energy use of appliances prediction

Subject

Appliances
Feature engineering
Long short-term memory
Principal component analysis
Prediction

Description

Electric energy consumption in a residential household is one of the key factors
that affect the overall national electricity demand. Household appliances are
one of the most electricity consumers in a residential household. Therefore, it
is crucial to make a proper prediction for the electricity consumption of these
appliances. This research implemented feature engineering technique and long
short-term memory (LSTM) as a model predictor. Principal component
analysis (PCA) was implemented as a feature extractor by reducing the final
62 features to 25 principal components for the LSTM inputs. Based on the
experiments, the two-layered LSTM model (composed by 25 and 20 neurons
for the first and second later respectively) with lookback number of 3 found to
give the best performance with the error rates of 62.013 and 26.982 for root
mean squared error (RMSE) and mean average error (MAE), respectively.

Creator

I Wayan Aditya Suranata, I Nyoman Kusuma Wardana, Naser Jawas, I Komang Agus Ady Aryanto

Source

http://journal.uad.ac.id/index.php/TELKOMNIKA

Date

Aug 31, 2020

Contributor

peri irawan

Format

pdf

Language

english

Type

text

Files

Collection

Tags

,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon ,

Citation

I Wayan Aditya Suranata, I Nyoman Kusuma Wardana, Naser Jawas, I Komang Agus Ady Aryanto, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Feature engineering and long short-term memory for energy use of appliances prediction,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/3817.