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Development and performance assessment of a new opensource Bayesian inference R platform for building energy model calibration

Author(s): Hou D; Zhan D; Wang L; Hassan IG; Sezer N;

Many factors contribute to the inherent uncertainty of energy consumption modeling in buildings. It is essential to perform a calibration and sensitivity analysis in order to manage these uncertainties. Despite the availability of several calibration methods, they are often deterministic and lack quantified uncertainties. Moreover, the selection of parame ...

Article GUID: 37936825


Development of a Bayesian inference model for assessing ventilation condition based on CO2 meters in primary schools

Author(s): Hou D; Wang LL; Katal A; Yan S; Zhou LG; Wang V; Vuotari M; Li E; Xie Z;

Outdoor fresh air ventilation plays a significant role in reducing airborne transmission of diseases in indoor spaces. School classrooms are considerably challenged during the COVID-19 pandemic because of the increasing need for in-person education, untimely and incompleted vaccinations, high occupancy density, and uncertain ventilation conditions. Many s ...

Article GUID: 36035815


Identification of point source emission in river pollution incidents based on Bayesian inference and genetic algorithm: Inverse modeling, sensitivity, and uncertainty analysis

Author(s): Zhu Y; Chen Z; Asif Z;

Identification of pollution point source in rivers is strenuous due to accidental chemical spills or unmanaged wastewater discharges. It is crucial to take physical characteristics into account in the estimation of pollution sources. In this study, an integrated inverse modeling framework is developed to identify a point source of accidental water polluti ...

Article GUID: 34380214


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