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Number of items: 4.

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
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Alammar, Ammar 2022. Investigating the impact of adaptive facades on energy performance using simulation and machine learning. PhD Thesis, Cardiff University.
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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
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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.
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