Robust probabilistic modelling of mould growth in building envelopes using random forests machine learning algorithm
Probabilistic methods can be used to account for uncertainties in hygrothermal analysis of building envelopes. This paper presents methods for robust mould reliability analysis and identification of critical parameters. Mould indices are calculated by probabilistic hygrothermal analysis, followed by the application of the "Finnish mould growth model." To increase the robustness of the mould growth