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Master's Dissertation
DOI
https://doi.org/10.11606/D.3.2006.tde-01042009-095125
Document
Author
Full name
Humberto Rodrigo Sandmann
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2006
Supervisor
Committee
Andrade, Marco Túlio Carvalho de (President)
Kobayashi, Guiou
Spina, Edison
Title in Portuguese
Predição não-linear de séries temporais usando sistemas de arquitetura neuro-fuzzy.
Keywords in Portuguese
Análise de séries temporais
Lógica fuzzy
Redes neurais
Sistemas híbridos
Abstract in Portuguese
Esta dissertação tem como objetivo a aplicação de sistemas com arquitetura neuro-fuzzy na predição de funções que geram séries temporais. A arquitetura pesquisada é a Adaptive Neuro-Fuzzy Inference System (ANFIS). Esta arquitetura se trata de um Fuzzy Inference Systems (FIS) im- plementado sob o paradigma das redes neurais artificiais. Ao fazer o uso da tecnologia de redes neurais artificiais, o ANFIS possui a capacidade de apren- dizagem dos dados do ambiente no qual está inserido. Da mesma forma, por implementar um FIS, o ANFIS agrega também a competência de processamento linguístico. Logo, o ANFIS pode ser categorizado como um sistema híbrido. Ao longo dos capítulos estão expostos alguns conceitos e fundamentos da Teoria Fuzzy, assim como das redes neurais artificiais e sistemas híbridos. Ao final do trabalho são realizadas algumas discussões, análises e conclusões, as quais permitem a possibilidade de futuras aplicações e extensão deste.
Title in English
Prediction of time series using architecture based on neuro-fuzzy systems.
Keywords in English
Fuzzy
Hibrid systems
Neural networks
Time series analyse
Abstract in English
This master dissertation has as main objetive applies systems of neuro-fuzzy architecture for functions prediction in serie times. The architecture carried out is the Adaptive Neuro-Fuzzy Inference System (ANFIS). This architecture is a kind of Fuzzy Inference Systems (FIS) implemen- tation under a paradigm of arti¯cial neural networks. Making use of technology of arti¯cial neural networks, the ANFIS has the capacity of learning with environ- ment data that inserted on. As the same, the ANFIS had been implemented to be a FIS. Then it can process simbolic variables. So, an ANFIS can be described like a hibrid system. All over the chapters are showed some concepts and fundaments of Fuzzy theory, arti¯cial neural networks and hidrid systems. The purpose of the tests the ANFIS, it were been made from a logistic function and a Mackey-Glass function. This tests were against with an estimation function made by MLP net. At the end of the work are some discussions, analyses and conclusions that allows futures possibilites of applications and extensions of this work.
 
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Publishing Date
2009-04-09
 
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