Visual-FIR: A Tool for Model Identification and Prediction
of Dynamical Complex Systems
Keywords
- Fuzzy systems
- Inductive reasoning
- Qualitative modeling
- Dynamical systems
- DAMADICS benchmark
Abstract
A new platform for the Fuzzy Inductive Reasoning (FIR) methodology has been
designed and developed under the MATLAB environment. The new tool, named Visual-FIR,
allows the identification of dynamic systems models in a user-friendly environment.
FIR offers a pattern-based approach to modeling and predicting either univariate or
multivariate time series, obtaining very good results when applied to various areas
such as control, biology, and medicine. However, the available implementation of FIR
was such that new code had to be developed for each new application studied. Visual-FIR
resolves this limitation and offers a high efficiency implementation. Furthermore, the
Visual-FIR platform presents a new vision of the methodology based on process blocks
and adds new features, increasing the overall capabilities of the FIR methodology. The
DAMADICS benchmark problem is addressed in this research using the Visual-FIR approach.
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Last modified: January 19, 2008 -- © François Cellier