ORCA
Online Research @ Cardiff
Browse by All Cardiff Authors
![[up]](/style/images/multi_up.png)
Up a levelNumber of items: 5.
Alammar, Ammar, Alymani, Abdulrahman and Jabi, Wassim  ORCID: https://orcid.org/0000-0002-2594-9568
2024.
Building energy efficiency estimations with random forest for single and multi-zones.
Presented at: eCAADe 2024 Conference,
Nicosia, Cyprus,
9-13 September 2024.
Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe.
, vol.2
Cyprus:
eCAADe,
pp. 365-374.
|
|
|
|
Alammar, Ammar and Jabi, Wassim ORCID: https://orcid.org/0000-0002-2594-9568
2023.
Generation of a large synthetic database of office tower’s energy demand using simulation and machine learning.
Presented at: 6th International Symposium on Formal Methods in Architecture (6FMA),
24-28 May 2022.
Published in: Mora, Plácido Lizancos, Viana, David Leite, Morais, Franklim and Vaz, Jorge Vieira eds.
Formal Methods in Architecture. FMA 2022. Digital Innovations in Architecture, Engineering and Construction.
Singapore:
Springer,
pp. 479-500.
10.1007/978-981-99-2217-8_27
|
|
|
|
Alammar, Ammar
2022.
Investigating the impact of adaptive facades on energy performance using simulation and machine learning.
PhD Thesis,
Cardiff University.
Item availability restricted. |
|
|
Alammar, Ammar and Jabi, Wassim ORCID: https://orcid.org/0000-0002-2594-9568
2022.
Predicting cooling energy demands of adaptive facades using artificial neural network.
Presented at: The 13th annual Symposium on Simulation for Architecture and Urban Design (SimAUD) with he Annual Modeling and Simulation Conference (ANNSIM),
San Diego State University, San Diego, CA, USA,
18-20 July 2022.
2022 Annual Modeling and Simulation Conference (ANNSIM).
IEEE,
pp. 656-669.
10.23919/ANNSIM55834.2022.9859413
|
|
|
|
Alammar, Ammar, Jabi, Wassim ORCID: https://orcid.org/0000-0002-2594-9568 and Lannon, Simon ORCID: https://orcid.org/0000-0003-4677-7184
2021.
Predicting incident solar radiation on building’s envelope using machine learning.
Presented at: 12th Symposium on Simulation for Architecture and Urban Design (SimAUD 2021),
Virtual,
15-17 April 2021.
|
|
|