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Title:
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Automatic construction of rules fuzzy for modelling and prediction of the central nervous system
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Author:
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Múgica Álvarez, Francisco; Nebot Castells, M. Àngela; Gómez Miranda, Pilar
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Ciències de la Computació; Universitat Politècnica de Catalunya. SOCO - Soft Computing |
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Abstract:
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The main goal of this work is to study the performance of
CARFIR (Automatic Construction of Rules in Fuzzy Inductive Reasoning)
methodology for the modelling
and prediction of the human central nervous system (CNS). The CNS
controls the hemodynamical system by generating the regulating signals
for the blood vessels and the heart. The main idea behind CARFIR is to
expand the capacity of the FIR methodology allowing it to work with
classical fuzzy rules. CARFIR is able to automatically construct fuzzy
rules starting from a set of pattern rules obtained by FIR. The new
methodology preserves as much as possible the knowledge of the pattern
rules in a compact fuzzy rule base. The prediction results obtained by
the fuzzy prediction process of CARFIR methodology are compared with
those of other inductive methodologies, i.e. FIR, NARMAX and neural
networks |
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Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica
-CARFIR
-Automatic construction of rules in fuzzy inductive reasoning |
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Rights:
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Document type:
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Article - Published version
Report |
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