A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
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 (author) / Pohoryles, Daniel A. (author) / Bournas, Dionysios A. (author)
2023-06-20
896566 byte
Conference paper
Electronic Resource
English
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