TY  - GEN 
AU  - Severiche Maury, Zurisaddai
AU  - Arrubla Hoyos, Wilson
AU  - Ramírez-Velarde, Raúl
AU  - Cama Pinto, Dora
AU  - Holgado Terriza, Juan Antonio
AU  - Damas Hermoso, Miguel
AU  - Cama Pinto, Alejandro
PY  - 2024
UR  - https://hdl.handle.net/10481/94594
AB  - 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...
LA  - eng
PB  - MDPI
KW  - Home energy management system (HEMS)
KW  - Artificial intelligence
KW  - Deep learning
TI  - LSTM Networks for Home Energy Efficiency
DO  - 10.3390/designs8040078
ER  -