id |
sigradi2023_396 |
authors |
Akdogan, Merve, Alaçam, Sema and Töreyin, Behçet Ugur |
year |
2023 |
title |
A Bayesian Model for Optimizing Thermal Comfort and Indoor Air Quality |
source |
García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 349360 |
summary |
This study focuses on the usage of a probabilistic approach on determining the best course of action in a specific environment within the domain of architecture. More specifically, Bayesian decision theory is applied on a simplified problem of maintaining thermal comfort and air quality. An already existing comprehensive dataset is used and narrowed down for the purpose of the study. Environment measurements (indoor and outdoor temperature, indoor CO2 level and air humidity) are taken as input variables and user preferences (open or closed window) are taken as outputs in order to address the problem as a binary classification problem. The paper can be regarded as a preliminary study on the usage of probabilistic approaches in the discipline of architecture. |
keywords |
Predictive Modeling, Binary Classification, Bayesian Decision Theory, Occupant-Building Interaction, Thermal Comfort |
series |
SIGraDi |
email |
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full text |
file.pdf (441,870 bytes) |
references |
Content-type: text/plain
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last changed |
2024/03/08 14:07 |
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