TY - CHAP A1 - Parzinger, Michael A1 - Schanda, Ulrich T1 - Analysis of spectra for sound insulation using methods of mathematical statistics and AI - first approaches T2 - Proceedings of Forum Acusticum 2023 N2 - Within the framework of a research focus at the TH Rosenheim on prediction methods for sound and impact sound insulation in timber constructions, methods of mathematical statistics and artificial intelligence are applied to sound insulation. To estimate the potential of those methods, one-third octave band spectra of measured sound insulation of sand-lime brickwork have been analyzed first. On selected data sets for certain building constructions, physically based calculation approaches according to the \backslashDIN{} series of standards, are compared with purely statistical methods such as GAMLSS (Generalized Additive Models for Location, Scale and Shape Parameters). The parameters derived from these procedures can be used for prediction purposes. The interval estimators resulting from these methods are compared. In addition, methods to classify the separating construction based on measurements are discussed. Thereby, in situ, measurements are used in addition to laboratory measurements. KW - Klassifikation KW - LDA/QDA KW - MLclassifier KW - Regression KW - Schall KW - SVM Y1 - 2023 ER -