Hybrid models in epidemiology

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Abstract

This book is devoted to the applications of fuzzy sets theory in epidemiology and correlated areas. However, as it is observed in other fields, it is becoming more and more common the use of the multiple and combined mathematical tools, aiming the treatment of complex problems in biomedical sciences. Usually the mixing of these different approaches involves classical mathematics and artificial intelligent theories, such as fuzzy systems, neural networks, evolutionary computation, expert systems, cellular automata, and so on. This kind of modeling, where several approaches are put working together, is called hybrid models. © 2008 Springer-Verlag Berlin Heidelberg.

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Massad, E., Ortega, N. R. S., de Barros, L. C., & Struchiner, C. J. (2008). Hybrid models in epidemiology. Studies in Fuzziness and Soft Computing, 232, 253–276. https://doi.org/10.1007/978-3-540-69094-8_12

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