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July 4, 2026Journal of Building Performance Simulation

Causal modelling of occupant window behaviour for indoor temperature prediction

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Authors

HKH KimUniversity of Science and TechnologySKS KimSeoul National UniversityCPCheol Soo ParkSeoul National University

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Overview

Randomized trial develops causality-based model for indoor temperature prediction in households, highlighting impactful occupant behaviour.

Key Points

  • This research aims to explain how occupant window behaviour influences indoor temperature through a causality-based model.
  • Developed a structural causal model (SCM) to represent window operation based on indoor conditions.
  • Utilized logistic regression to analyze window-opening behaviour data from four households in Seoul, South Korea.
  • Compared SCM with correlation-based model to evaluate the effectiveness of causal modelling.
  • Both SCM and correlation-based models had comparable goodness-of-fit.
  • Household-specific window-opening thresholds varied from 21.60 to 28.02 °C.
  • The SCM indicated a counterfactual case that demonstrated a 0.154 °C temperature change under alternative window-opening behaviour.

Cite This Study

Kim et al. (2026) studied this question.

synapsesocial.com/papers/6a48a29489561a0c2d78d199https://doi.org/10.1080/19401493.2026.2695416
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