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

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 dependen...

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Bibliographic Details
Published inApplications of Fuzzy Sets Theory Vol. 4578; pp. 53 - 60
Main Authors Sangiovanni, Guido, Lavagna, Michèle
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2007
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Artificial intelligence
Causal Dependency
Chaotic Time Series
Exhaustive Search
Hill Climbing
Mathematical theory of computation
Quality Index
User interface design & usability
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Summary: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.
ISBN:9783540733997
354073399X
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-73400-0_7