LSTM Networks for Home Energy Efficiency

This study aims to develop and evaluate an LSTM neural network for predicting household energy consumption. To conduct the experiment, a testbed was created consisting of five common appliances, namely, a TV, air conditioner, fan, computer, and lamp, each connected to individual smart meters within...

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Bibliographic Details
Published in:	Designs
Main Authors:	Zurisaddai Severiche-Maury, Wilson Arrubla-Hoyos, Raul Ramirez-Velarde, Dora Cama-Pinto, Juan Antonio Holgado-Terriza, Miguel Damas-Hermoso, Alejandro Cama-Pinto
Format:	Article
Language:	English
Published:	MDPI AG 2024-08-01
Subjects:	home energy management system (HEMS) artificial intelligence deep learning LSTM energy efficiency
Online Access:	https://www.mdpi.com/2411-9660/8/4/78

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