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.
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© 2008 Springer-Verlag Berlin Heidelberg
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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
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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
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