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Master's Dissertation
DOI
10.11606/D.18.2016.tde-28112016-162338
Document
Author
Full name
Fabio Lavôr Teixeira
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2003
Supervisor
Committee
Reis, Luisa Fernanda Ribeiro (President)
Barbosa, Paulo Sérgio Franco
Chaudhry, Fazal Hussain
Title in Portuguese
Modelagem de séries fluviométricas para o semi-árido brasileiro via redes neurais artificiais
Keywords in Portuguese
Modelagem de vazões
Redes neurais artificiais
Séries fluviométricas
Abstract in Portuguese
As Redes Neurais Artificiais (RNAs) vêm sendo empregadas com cada vez mais sucesso em diversas áreas de pesquisa, no campo da engenharia e em outros campos diversos. Neste trabalho foram modeladas séries fluviométricas relativas às afluências a quatro reservatórios, localizados em quatro bacias hidrográficas distintas que compõem a Bacia Metropolitana de Fortaleza, Ceará, Brasil. Tais afluências apresentam peculiaridades relativas à ocorrência de magnitudes nulas, que dificultam sua modelagem através dos convencionais modelos estatísticos da família Box-Jenkins. Neste estudo foram trabalhadas duas abordagens distintas, a primeira univariada, em que cada série era modelada de forma individual, e a segunda multivariada, em que as séries fluviométricas eram modeladas simultaneamente. Os resultados obtidos, segundo ambas as modelagens, demonstram que a técnica apresenta potencial para a aplicação pretendida. Estudos futuros merecem ser desenvolvidos ainda no sentido de verificar a melhor maneira de se enquadrar a componente aleatória nas séries sintéticas produzidas via RNAs.
Title in English
Discharge time series modeling applied to rivers from Northeast of Brazil using artificial neural networks
Keywords in English
Artificial neural networks
Discharge modeling
Discharge time series
Abstract in English
Artificial Neural Networks (ANNs) are being used more and more in many different fields of research, in engineering applications or other applications. This research deals with modeling of inflows to four reservoirs, located in different watersheds that belong to the Metropolitan Watershed of Fortaleza city, Brazil. These discharge sequences have particular characteristics in that they have frequent occurence of null discharges which makes it difficult to use traditional statistical models such as those Box-Jenkis family. Two different modeling approaches were adopted in this study, the first univariate, in which each time series was modeled individually, and the second multivariate, in which the four time series were modeled simultaneously. The results from the both approaches show that the technique has potential for use in water resources planning and management. Future studies are required to propose better means of incorporing the random component in the generation of synthetic time series through ANNs.
 
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Publishing Date
2016-11-28
 
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