Using Autonomous Outlier Detection Methods for Thermophysical Property Data
Andrea Schnorr,
Daniel Johannes Kaldi,
Jens Staubach
et al.
Abstract:The reliability and accuracy of thermophysical property data are of central importance for the development of models that describe these properties. In this work, we compare different autonomous algorithms for identifying the outliers in an existing database. Therefore, the comprehensive database on thermophysical property data for the Lennard-Jones fluid [J. Chem. Inf. Model. 2019, 59, 4248−4265] is used. We focus on homogeneous state property data at given temperature and density for the pressure p, thermal… Show more
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