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A systematic and general machine learning approach to build a consistent data set from different experiments

By Matheus Máximo-Canadas and others at
LogoInstituto Militar de Engenharia
and
LogoUniversidade Federal Fluminense
Experimental data from different sources present challenges due to variability and noise from various experimental conditions, apparatuses, and environmental factors. In this work, we propose a general method to address these challenges to build a consistent data set employing different thermal conductivity experimental data sets of methane from the liquid,... Show more
July 10, 2024
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A systematic and general machine learning approach to build a consistent data set from different experiments
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