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Fuzzy Rule-Based Models in Epidemiology

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

Abstract

Mathematical models are, in essence, theoretical structures that describe the behavior of real systems through the quantification and manipulation of variables. These models have been widely applied in several areas, aiming to the elaboration of forecasts, analysis of information, treatment of data, control of systems, and evaluation of hypotheses and strategies. In this sense, mathematical modeling have importantly contributed to decision making process. Chapter 3 presents an overview of mathematical modeling and its aspects in epidemiology, introducing the basic concepts of some classic models, that is, models based on the classical logic axioms, and discuss the problems to modeling uncertainties when a more realistic scenario is considered.

Keywords

Membership Function Fuzzy Rule Fuzzy Model Linguistic Term Fuzzy Relation 
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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