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

2016/05/19 by Khadija Tijani, Stephane Ploix, Tijani, Khadija +9
Computer Science · Engineering · Environmental Science · #Artificial Intelligence (cs.AI) #Building Energy and Comfort Optimization #FOS: Computer and information sciences #Indoor Air Quality and Microbial Exposure #Wind and Air Flow Studies #cs.AI

paper · pdf · doi:10.48550/arxiv.1605.05966

IBPSA India 2015, Dec 2015, Hyderabad, India. arXiv admin note: substantial text overlap with arXiv:1510.01970

arxiv created 2016/05/19 · openalex publication_date 2016/05/19 · arxiv updated 2016/05/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

Citations

• Towards a general framework for an observation and knowledge based model of occupant behaviour in office buildings

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