Analyzing the Sars-Cov-2 Pandemic Outbreak Using Fuzzy Sets and the SIR Model
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-16038-7_5
Reference22 articles.
1. Cecconello, M., Dorini, F., Haeser, G.: On fuzzy uncertainties on the logistic equation. Fuzzy Sets Syst. 328, 107–121 (2017)
2. Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1, 3–28 (1978)
3. de Barros, L.C., Bassanezi, R.C., Lodwick, W.A.: A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics. Springer, Berlin Heidelberg (2017). https://doi.org/10.1007/978-3-662-53324-6
4. Melin, P., Monica, J.C., Sanches, D., Castilho, O.: Multiple ensemble neural network models with fuzzy response aggregation for predicting COVID-19 time series: the case of Mexico. Healthcare 8(2) (2020)
5. Castilho, O., Melin, P.: Forecasting of COVID-19 time series for countries in the world based on a hybrid approach combining the fractal dimension and fuzzy logic. Chaos, Solitons Fractals 140 (2020)
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