Reconstruction of the Matrix of Causal Dependencies for the Fuzzy Inductive Reasoning Method

Abstract

Fuzzy Inductive Reasoning (FIR) methodology is a very powerful tool for creating a mixed qualitative-quantitative model of any dynamical system by using its input and output signals. One of the key issue of this methodology is the creation of the mask, i.e. a matrix that contains the causal dependencies among the signals of the systems for particular time steps. This paper describes the ARMS – Automatic Reconstruction of the Mask Scheme – methodology that gives the opportunity of creating a sub-optimal mask with very good performances without an exhaustive search in the space of all the possibilities. This methodology has been validated on a wide class of dynamical system (from LTI systems to chaotic time series) and it has been compared to other methods proposed in literature.