Dynamic Bayesian Networks to simulate occupant behaviours in office buildings related to indoor air quality

Khadija Tijani (1, 2, 3) , Stéphane Ploix (3) , Benjamin Haas (1) , Julie Dugdale (2) , Quoc Dung Ngo (4)

1 CSTB - Centre Scientifique et Technique du Bâtiment
2 MAGMA - Modélisation d’agents autonomes en univers multi-agents
3 G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production
4 Post and Telecommunication Institut of Technology, Hanoi, Vient Nam

This paper proposes a new general approach based on Bayesian networks to model the human behaviour. This approach represents human behaviour with probabilistic cause-effect relations based on knowledge, but also with conditional probabilities coming either from knowledge or deduced from observations. This approach has been applied to the co-simulation of the CO2 concentration in an office coupled with human behaviour.

Mots clés: Dynamic Bayesian network; occupant behavior; building simulation

Domaines: Intelligence artificielle [cs.AI]; Modélisation et simulation; Energie électrique

Khadija Tijani, Stéphane Ploix, Benjamin Haas, Julie Dugdale, Quoc Dung Ngo. Dynamic Bayesian Networks to simulate occupant behaviours in office buildings related to indoor air quality. IBPSA India 2015, Dec 2015, Hyderabad, India. ⟨hal-01317167⟩