A GPU-accelerated adaptation of the PSO algorithm for multi-objective optimization applied to artificial neural networks to predict energy consumption

Optimization research often confronts the challenge of developing time consuming processes. This article introduces an innovative approach that leverages the computational power of Graphics Processing Units (GPUs) to speed up that optimization process. We present an innovative adaptation of Particle...

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Bibliographic Details

Published in:	Applied soft computing Vol. 160; p. 111711
Main Authors:	Iruela, J.R.S., Ruiz, L.G.B., Criado-Ramón, D., Pegalajar, M.C., Capel, M.I.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.07.2024
Subjects:	Artificial neural networks Energy consumption prediction GPU/CUDA Model optimization Multi-objective algorithm Model optimization Energy consumption prediction Multi-objective algorithm GPU/CUDA Artificial neural networks
ISSN:	1568-4946, 1872-9681
Online Access:	Get full text
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