Automatic construction of fuzzy rules for modelling and prediction of the central nervous system

Fernando Vázquez, Pilar Gómez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.CARFIR is able to automatically construct fuzzy rules starting from a set of pattern rules obtained by FIR. The 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.

Original languageEnglish
Title of host publicationPattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings
PublisherSpringer Verlag
Pages443-450
Number of pages8
EditionPART 1
ISBN (Print)9783540728467
DOIs
StatePublished - 2007
Event3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007 - Girona, Spain
Duration: 6 Jun 20078 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4477 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007
Country/TerritorySpain
CityGirona
Period6/06/078/06/07

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