Forecasting of individual electricity consumption using Optimized Gradient Boosting Regression with Modified Particle Swarm Optimization-Reference-Cited by-同舟云学术

Forecasting of individual electricity consumption using Optimized Gradient Boosting Regression with Modified Particle Swarm Optimization

Published:2021-10 Issue: Volume:105 Page:104440
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Sepulveda Luis F.M.,Diniz Petterson S.,Diniz João O.B.,Netto Stelmo M.B.^ORCID,Cipriano Carolina L.S.,Araújo Alexandre C.^ORCID,Lemos Victor H.B.,Pessoa Alexandre C.P.^ORCID,Quintanilha Darlan B.P.^ORCID,Almeida João D.S.^ORCID,Silva Aristófanes C.,Paiva Anselmo C.,Braz Geraldo,Silva Márcia I.A.,Monteiro Eliana M.G.,Silva Italo F.S.,Fernandes Eduardo C.

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference35 articles.

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3. A gradient boosting regression based approach for energy consumption prediction in buildings;Bataineh;Adv. Energy Res.,2019

4. Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression;Ben Taieb;IEEE Trans. Smart Grid,2016

5. Monthly energy consumption forecast: A deep learning approach;Berriel,2017

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