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

Abstract

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.
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Dates and versions

hal-01317167 , version 1 (19-05-2016)

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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⟩
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