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Hierarchical Calibration of Archetypes For Urban Building Energy Model by feselistre is a document available to read on EtoBox.

The paper presents a hierarchical calibration framework for urban building energy modeling using archetypes, emphasizing the importance of avoiding oversimplified approaches that can lead to inferior predictive capabilities. It employs Bayesian inference techniques to propagate uncertainty throughout the calibration process, allowing for better estimation of archetype parameters by pooling information from training buildings. The framework is demonstrated with case-study data from the Danish residential bui

Author
feselistre
Language
EN