Prediction of Building’s Thermal Performance Using LSTM and MLP Neural Networks

Prediction of Building’s Thermal Performance Using LSTM and MLP Neural Networks

Accurate prediction of building indoor temperatures and thermal demand is of great help to control and optimize the energy performance of a building. However, building thermal inertia and lag lead to complex nonlinear systems is difficult to model. In this context, the application of artificial neur...

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Bibliographic Details
Main Authors: Miguel Martínez Comesaña, Lara Febrero-Garrido, Francisco Troncoso-Pastoriza, Javier Martínez-Torres
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Applied Sciences
Subjects:
neural network
LSTM
MLP
thermal inertia
building performance
Online Access:https://www.mdpi.com/2076-3417/10/21/7439

Internet

https://www.mdpi.com/2076-3417/10/21/7439

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