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Fuzzy Rule-Based Dynamical Models

  • Eduardo Massad
  • Neli Regina Siqueira Ortega
  • Laecio Carvalho de Barros
  • Claudio José Struchiner
Chapter
  • 940 Downloads
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 232)

Abstract

Epidemic dynamical systems theorists have been facing several hurdles in trying to validate their models, in particular due to several uncertainties related to variables, initial states and parameters values. These should ideally be taken from experimental work which are, quite to the contrary, demonstrating the extreme vagueness in the definition of such concepts like the force of infection, contact patterns or infected status. Therefore, a possible alternative approach could be the combination of fuzzy logic techniques with non-linear dynamical systems in order to provide a comprehensive analysis and the development of predictive tools in the epidemiology of infectious diseases.

Keywords

Membership Function Fuzzy Rule Fuzzy Model Extension Principle Triangular Membership Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Eduardo Massad
    • 1
  • Neli Regina Siqueira Ortega
    • 1
  • Laecio Carvalho de Barros
    • 2
  • Claudio José Struchiner
    • 3
  1. 1.The University of São Paulo, São PauloBrazil
  2. 2.State University of Campinas, CampinasBrazil
  3. 3.PROCC, Rio de JaneiroBrazil

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