Licenciatura em Matemática (Sede)
URI permanente desta comunidadehttps://arandu.ufrpe.br/handle/123456789/24
Siglas das Coleções:
APP - Artigo Publicado em Periódico
TAE - Trabalho Apresentado em Evento
TCC - Trabalho de Conclusão de Curso
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Resultados da Pesquisa
Item Modelos matemáticos epidemiológicos do tipo SIS e SIR e o segundo método de Lyapunov(2023-05-05) Santos, Letícia Maria Menezes dos; Didier, Maria Ângela Caldas; Freitas, Lorena Brizza Soares; http://lattes.cnpq.br/2302580820419163; http://lattes.cnpq.br/9721552594807972; http://lattes.cnpq.br/9115322351374062This work aims to study epidemiological mathematical models of the SIS (Susceptible- Infected-Susceptible) and SIR (Susceptible-Infected-Removed) types, focusing on the stability of the equilibrium points of the differential equation systems that describe them. Stability analysis will be presented in two ways, using the eigenvalue characteristics and/or the trace of the system matrix and using the Second Lyapunov Method. We also address the stability of variations of these models, considering non-constant total population and vital dynamics (births and deaths), or dividing the population of infected individuals into exposed individuals (infected who do not yet transmit the disease) and infectious individuals (infected who transmit the disease). We define the Basic Reproduction Value, and for some models, we present ways to obtain it from the involved rates and initial conditions of the system. A calculation that determines the maximum number of infected individuals reached was performed for the SIR model with constant total population and without vital dynamics. Finally, to understand how these models are practically applied, we decided to study the evolution of the COVID-19 pandemic in the state of Pernambuco in 2020 and 2021 through the SIR model with constant population size and no vital dynamics. To do this, we calculated the Basic Reproduction Value and the maximum number of infected individuals for each case. It is worth noting that an evolutionary algorithm was used to obtain a model that best approximated the real data.Item Um estudo sobre equações diferenciais ordinárias em dinâmica populacional(2019-12-14) Franco, Mariana Pereira; Carvalho, Gilson Mamede de; http://lattes.cnpq.br/0044877127514130; http://lattes.cnpq.br/1514122794309246In this work we will emphasize a modeling by differential equations for the dynamics between two populations in a predation relation, which is known in the literature as Volterra’s Predator-Prey Model. With this purpose, we will present necessary mathematical tools for a proper problem analysis: a brief study of the solution methods for some ordinary differential equations, the results that underlie them and some aplications; and notions of stability of singularities of autonomous systems.Item Técnicas de Modelagem Matemática e os Métodos de Runge-Kutta(2021-07-23) Silva, Angelo Antunes da Rocha; Didier, Maria Ângela Caldas; Gondim, João Antônio Miranda; http://lattes.cnpq.br/2674397127545655; http://lattes.cnpq.br/9721552594807972; http://lattes.cnpq.br/9069459979748516This work consists in the study of Mathematical Modeling with numerical analysis of the models. In it we present the steps of a modeling process, define and evaluate a mathematical model and also discuss the technique of modeling by fitting curves through the Minimal Squares Method, as well as by differential equations where we approach some models, among them those which describe a populational growth dynamic and epidemiological models. We also present the methods from Taylor Series and Runge-Kutta for the construction of numeric solutions for a initial value problem. As the main contribution we simulated analytical and numerical solutions for four problems of initial value, analysing the error linked to numerical solutions, aiming to answer questions related to the general formula of the Runge-Kutta method of order 2. To calculate error for a certain range we used L2 norm and a closed formula from Newton-Cotes. The purpose here is to offer material in the subject of Mathematical Modeling which can be used by Mathematics Graduation students as another area that utilizes Differential Calculus as a tool. The simulations were coded using Python and the code may be accessed through the link in the beggining of this essay.