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
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Massad, E., Ortega, N.R.S., de Barros, L.C., Struchiner, C.J. (2008). Fuzzy Rule-Based Dynamical Models. In: Fuzzy Logic in Action: Applications in Epidemiology and Beyond. Studies in Fuzziness and Soft Computing, vol 232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69094-8_8
Download citation
DOI: https://doi.org/10.1007/978-3-540-69094-8_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69092-4
Online ISBN: 978-3-540-69094-8
eBook Packages: EngineeringEngineering (R0)