On applications of stochastic differential equations

Detalhes bibliográficos
Ano de defesa: 2025
Autor(a) principal: Farias, Filipe Pereira de
Orientador(a): Mulas, Michela
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Área do conhecimento CNPq:
Link de acesso: http://repositorio.ufc.br/handle/riufc/82345
Resumo: The study of dynamic systems represents a large field of mathematics that models the temporal evolution of phenomena in real life. The theory of differential equations largely deals with the modeling of these systems through the laws that govern the temporal rates at which the states describing dynamic systems change. In this context, we study those models in which a random factor is considered in the law that governs the rate of change of these systems over time. These are called stochastic differential equations. This work briefly presents the mathematical theory underlying this type of differential equation by constructing an analogy between the theory of ordinary differential equations and that of stochastic ones. Finally, and as the main objective, two applications of the theory are presented in problems at the state of the art: stochastic thermodynamics and probabilistic numerical methods. The first deals with an attempt to extend the classical theory of thermodynamics of equilibrium systems to systems out of equilibrium, such as chemical reactions presented in this work, for example. In the second problem, stochastic differential equations are used to probabilistically model numerical algorithms for solving ordinary differential equations, which can even account for uncertainties that the modeler might have regarding the system to be studied. These theories are reviewed and applied to systems already known in the literature. In the case of stochastic thermodynamics, we apply the theory to the study of enzymatic reactions governed by the Michaelis-Menten mechanism. For probabilistic numerical methods, we apply the theory to try to identify the parameters of a bioreactor model, which is part of a model of pilot wastewater treatment plant used as a test bench for water treatment systems.
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spelling Farias, Filipe Pereira deMulas, Michela2025-09-02T18:08:27Z2025-09-02T18:08:27Z2025FARIAS, Filipe Pereira de. On applications of stochastic differential equations. 2025. 114f. Dissertação (Mestrado em Engenharia de Teleinformática) – Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2025.http://repositorio.ufc.br/handle/riufc/82345The study of dynamic systems represents a large field of mathematics that models the temporal evolution of phenomena in real life. The theory of differential equations largely deals with the modeling of these systems through the laws that govern the temporal rates at which the states describing dynamic systems change. In this context, we study those models in which a random factor is considered in the law that governs the rate of change of these systems over time. These are called stochastic differential equations. This work briefly presents the mathematical theory underlying this type of differential equation by constructing an analogy between the theory of ordinary differential equations and that of stochastic ones. Finally, and as the main objective, two applications of the theory are presented in problems at the state of the art: stochastic thermodynamics and probabilistic numerical methods. The first deals with an attempt to extend the classical theory of thermodynamics of equilibrium systems to systems out of equilibrium, such as chemical reactions presented in this work, for example. In the second problem, stochastic differential equations are used to probabilistically model numerical algorithms for solving ordinary differential equations, which can even account for uncertainties that the modeler might have regarding the system to be studied. These theories are reviewed and applied to systems already known in the literature. In the case of stochastic thermodynamics, we apply the theory to the study of enzymatic reactions governed by the Michaelis-Menten mechanism. For probabilistic numerical methods, we apply the theory to try to identify the parameters of a bioreactor model, which is part of a model of pilot wastewater treatment plant used as a test bench for water treatment systems.O estudo de sistemas dinâmicos representa um grande campo da matemática que modela a evolução temporal de fenômenos na vida real. A teoria de equações diferenciais lida em grande parte com a modelagem desses sistemas pelas leis que regem as taxas temporais nas quais os estados que descrevem os sistemas dinâmicos variam. Nesse âmbito, estudamos aquelas modelagens na qual um fator aleatório é considerado na lei que que rege a taxa de variação temporal desses sistemas. A estas damos os nomes de equações diferenciais estocásticas. Nesse trabalho é apresentado superficialmente a teoria matemática que fundamenta esse tipo de equação diferencial, através da construção de uma analogia entre a teoria de equações diferenciais ordinárias e daquelas estocásticas. Por fim, e como maior objetivo, são apresentadas duas aplicações da teoria em problemas que estão no estado da arte: termodinâmica estocástica e cálculo numérico probabilístico. O primeiro trata de uma tentativa de extensão da teoria clássica de termodinâmica de sistemas em equilíbrio para sistemas fora do equilíbrio, no caso deste trabalho por exemplo, em reações químicas. No segundo problema, as equações diferenciais estocásticas são utilizadas para modelar probabilisticamente algoritmos numéricos de solução de equações diferenciais ordinárias, podendo até compreender incertezas que o modelador tenha a respeito do sistema a ser estudado. Estas teorias são revisadas e aplicadas em sistemas já conhecidos na literatura. No caso da termodinâmica estocástica, aplicamos a teoria ao estudo de reações enzimáticas regidas pelo mecanismo de Michaelis-Menten. Já para o cálculo numérico probabilistico, aplicamos a teoria para tentar identificar os parâmetros do modelo de um bioreator, este integrante de um modelo planta piloto de tratamento de água residual utilizado como de referência para sistemas de tratamento de água.Este documento está disponível online com base na Portaria no 348, de 08 de dezembro de 2022, disponível em: https://biblioteca.ufc.br/wp-content/uploads/2022/12/portaria348-2022.pdf, que autoriza a digitalização e a disponibilização no Repositório Institucional (RI) da coleção retrospectiva de TCC, dissertações e teses da UFC, sem o termo de anuência prévia dos autores. Em caso de trabalhos com pedidos de patente e/ou de embargo, cabe, exclusivamente, ao autor(a) solicitar a restrição de acesso ou retirada de seu trabalho do RI, mediante apresentação de documento comprobatório à Direção do Sistema de Bibliotecas.On applications of stochastic differential equationsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisEquações diferenciais estocásticasTermodinâmica estocásticaComputação numéricaComputação numérica probabilísticaProcessos GaussianosSistemas dinâmicosStochastic differential equationsStochastic thermodynamicsNumerical computationProbabilistic numerical calculationGaussian processesDynamic systemsCNPQ::ENGENHARIAS::ENGENHARIA ELETRICAinfo:eu-repo/semantics/openAccessengreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFChttps://orcid.org/0000-0003-1585-3682http://lattes.cnpq.br/6368190257547403http://lattes.cnpq.br/08354088980768752025-08-20ORIGINAL2025_dis_fpfarias.pdf2025_dis_fpfarias.pdfDissertaçãoapplication/pdf2896892http://repositorio.ufc.br/bitstream/riufc/82345/1/2025_dis_fpfarias.pdf4d75bca352255c68bb32dd50ce8ff165MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.ufc.br/bitstream/riufc/82345/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52riufc/823452025-09-02 15:09:31.853oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2025-09-02T18:09:31Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.pt_BR.fl_str_mv On applications of stochastic differential equations
title On applications of stochastic differential equations
spellingShingle On applications of stochastic differential equations
Farias, Filipe Pereira de
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
Equações diferenciais estocásticas
Termodinâmica estocástica
Computação numérica
Computação numérica probabilística
Processos Gaussianos
Sistemas dinâmicos
Stochastic differential equations
Stochastic thermodynamics
Numerical computation
Probabilistic numerical calculation
Gaussian processes
Dynamic systems
title_short On applications of stochastic differential equations
title_full On applications of stochastic differential equations
title_fullStr On applications of stochastic differential equations
title_full_unstemmed On applications of stochastic differential equations
title_sort On applications of stochastic differential equations
author Farias, Filipe Pereira de
author_facet Farias, Filipe Pereira de
author_role author
dc.contributor.author.fl_str_mv Farias, Filipe Pereira de
dc.contributor.advisor1.fl_str_mv Mulas, Michela
contributor_str_mv Mulas, Michela
dc.subject.cnpq.fl_str_mv CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
topic CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
Equações diferenciais estocásticas
Termodinâmica estocástica
Computação numérica
Computação numérica probabilística
Processos Gaussianos
Sistemas dinâmicos
Stochastic differential equations
Stochastic thermodynamics
Numerical computation
Probabilistic numerical calculation
Gaussian processes
Dynamic systems
dc.subject.ptbr.pt_BR.fl_str_mv Equações diferenciais estocásticas
Termodinâmica estocástica
Computação numérica
Computação numérica probabilística
Processos Gaussianos
Sistemas dinâmicos
dc.subject.en.pt_BR.fl_str_mv Stochastic differential equations
Stochastic thermodynamics
Numerical computation
Probabilistic numerical calculation
Gaussian processes
Dynamic systems
description The study of dynamic systems represents a large field of mathematics that models the temporal evolution of phenomena in real life. The theory of differential equations largely deals with the modeling of these systems through the laws that govern the temporal rates at which the states describing dynamic systems change. In this context, we study those models in which a random factor is considered in the law that governs the rate of change of these systems over time. These are called stochastic differential equations. This work briefly presents the mathematical theory underlying this type of differential equation by constructing an analogy between the theory of ordinary differential equations and that of stochastic ones. Finally, and as the main objective, two applications of the theory are presented in problems at the state of the art: stochastic thermodynamics and probabilistic numerical methods. The first deals with an attempt to extend the classical theory of thermodynamics of equilibrium systems to systems out of equilibrium, such as chemical reactions presented in this work, for example. In the second problem, stochastic differential equations are used to probabilistically model numerical algorithms for solving ordinary differential equations, which can even account for uncertainties that the modeler might have regarding the system to be studied. These theories are reviewed and applied to systems already known in the literature. In the case of stochastic thermodynamics, we apply the theory to the study of enzymatic reactions governed by the Michaelis-Menten mechanism. For probabilistic numerical methods, we apply the theory to try to identify the parameters of a bioreactor model, which is part of a model of pilot wastewater treatment plant used as a test bench for water treatment systems.
publishDate 2025
dc.date.accessioned.fl_str_mv 2025-09-02T18:08:27Z
dc.date.available.fl_str_mv 2025-09-02T18:08:27Z
dc.date.issued.fl_str_mv 2025
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv FARIAS, Filipe Pereira de. On applications of stochastic differential equations. 2025. 114f. Dissertação (Mestrado em Engenharia de Teleinformática) – Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2025.
dc.identifier.uri.fl_str_mv http://repositorio.ufc.br/handle/riufc/82345
identifier_str_mv FARIAS, Filipe Pereira de. On applications of stochastic differential equations. 2025. 114f. Dissertação (Mestrado em Engenharia de Teleinformática) – Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2025.
url http://repositorio.ufc.br/handle/riufc/82345
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
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reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
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