Author(s)

A.C. Capelo, L. Ironi & S. Tentoni

Abstract

Automated interpretation of experimental data is a necessary component in automated model building environments, i.e. tools capable to select a model which explains the observed behavior of a physical system. This paper describes an algorithm for the qualitative interpretation of experi- mental data whose goal is to single out the qualitative properties which characterize the behavior of a real physical system, and, consequently, to make a guess for a set of plausible candidate models of the phenomenon under study. We consider observations which are gathered from creep and relaxation experiments on visco-elastic materials. In this specific context, the interpretation problem consists in determining rules for the conversion of the numerical data into the specific qualitative properties which char

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