Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Simulation of EU building stock energy performance through artificial neural networks
This study proposes an efficient solution for accurate and reliable space heating energy demand simulation of the EU building stock. It relies on an artificial neural network model trained on building energy model simulations using a minimal number of input parameters. The performance parameters and the energy demand simulations showed a high accuracy and robustness of the developed tool, with a potential to be further used in assessing the impact of building renovation in the future.
Simulation of EU building stock energy performance through artificial neural networks
This study proposes an efficient solution for accurate and reliable space heating energy demand simulation of the EU building stock. It relies on an artificial neural network model trained on building energy model simulations using a minimal number of input parameters. The performance parameters and the energy demand simulations showed a high accuracy and robustness of the developed tool, with a potential to be further used in assessing the impact of building renovation in the future.
Simulation of EU building stock energy performance through artificial neural networks
Veljkovic, Ana (Autor:in) / Pohoryles, Daniel A. (Autor:in) / Bournas, Dionysios A. (Autor:in)
20.06.2023
896566 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Prediction of building energy consumption by using artificial neural networks
Tema Archiv | 2009
|On-line building energy prediction using adaptive artificial neural networks
Online Contents | 2005
|Simulation of Heat Exchanger Performance by Artificial Neural Networks
Taylor & Francis Verlag | 1999
|Runoff Simulation Using Artificial Neural Networks
British Library Conference Proceedings | 1993
|