Establishing a common data base of ice experiments and using machine learning to understand and predict ice behavior

Abstract

Machine learning and statistical tools are applied to identify how parameters, such as temperature, influence peak stress and ice behavior. To enable the analysis, a common and small scale experimental data base is established.