Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Electricity consumption forecasting based on ensemble deep learning with application to the Algerian market

Creator:
D. J. A. A.
Publisher:
Elsevier BV
Host:

Visit

doi.org

Languages

Arabic, Algerian Spoken

Licenses

https://www.elsevier.com/tdm/userlicense/1.0/https://www.elsevier.com/legal/tdmrep-licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/

Similar

Demand-Supply Forecasting based on Deep Learning for Electricity Balance in CameroonEfficient Electricity Consumption Tracking based on Machine LearningFORECASTING ELECTRICITY CONSUMPTION OF RESIDENTIAL USERS BASED ON LIFESTYLE DATA USING ARTIFICIAL NEURAL NETWORKSA Comparative Study of Forecasting Electricity Consumption Using Machine Learning ModelsA genetic programming-based ensemble method for long-term electricity demand forecastingFraud Detection of the Electricity Consumption by combining Deep Learning and Statistical Methods

Demand-Supply Forecasting based on Deep Learning for Electricity Balance in Cameroon

Electricity is becoming an important commodity in Cameroon. Within the years, its consumption and pr

Efficient Electricity Consumption Tracking based on Machine Learning

Efficient Electricity Consumption Tracking based on Machine Learning

Poster presented at the Deep Learning Indaba 2022 by Khutso FENYANE

FORECASTING ELECTRICITY CONSUMPTION OF RESIDENTIAL USERS BASED ON LIFESTYLE DATA USING ARTIFICIAL NEURAL NETWORKS

Electricity is the lifeline of almost everything in this 21st century. Residential electricity consu

A Comparative Study of Forecasting Electricity Consumption Using Machine Learning Models

Production of electricity from the burning of fossil fuels has caused an increase in the emission of

A genetic programming-based ensemble method for long-term electricity demand forecasting

This study introduces a novel genetic programming-based ensemble method for forecasting long-term el

Fraud Detection of the Electricity Consumption by combining Deep Learning and Statistical Methods

An important issue for the electricity distribution companies is the non-technical loss (NTL), also