Data: 23 de junho de 2025

Horário: 14h30

Local: sala 132 do bloco A – IME

Transmissão: meet.google.com/awz-asms-jnu

Resumo

The study proposes an integrated approach of fractional calculus and fuzzy logic to enhance epidemiological models. First, a new formulation of the fractional operators is presented, showing that they can be interpreted as weighted averages of past values of the classical operators. Interesting results arise from this formulation, such as the finding that lower fractional orders intensify the memory effect in the system. Next, a fuzzy logic concept, known as the triangular norm, is incorporated to model the encounters between individuals in the SIR model, enabling the consideration of control measures and yielding improved results. Finally, elements of fuzzy set theory are applied to quantify the uncertainty inherent in disease propagation. The results are illustrated through applications using real COVID-19 data.