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Master's Dissertation
DOI
10.11606/D.18.2003.tde-09112003-191558
Document
Author
Full name
Maurílio Benite
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2003
Supervisor
Committee
Nagano, Marcelo Seido (President)
Merlo, Edgard Monforte
Moccellin, Joao Vitor
Title in Portuguese
Aplicação de modelos de redes neurais na elaboração e análise de cenários macroeconômicos
Keywords in Portuguese
cenários e complexidade
dados macroeconômicos
redes neurais auto organizadas
Abstract in Portuguese
Este estudo versa sobre uma investigação de viabilidade da utilização de redes neurais auto-organizadas na classificação e exploração de dados macroeconômicos. Para tanto, foi elaborado um método no qual foram empregadas topologias neurais auto-organizadas, procurando assim explorar as características de melhor desempenho de cada um dos modelos, sob um enfoque seqüencial e com o intuito de se adquirir conhecimento intermediário em cada uma de suas fases, diminuindo o impacto da complexidade tanto no tempo requerido para realização da tarefa quanto na análise dos resultados. Os próprios resultados obtidos sugerem que a utilização de redes neurais artificiais auto-organizadas na aquisição de conhecimento sobre bases de dados aplicáveis às Ciências Econômicas apresenta desempenho análogo aos modelos paramétricos tradicionalmente empregados na construção de cenários com tais informações.
Title in English
Application of neural network models in macroeconomic scenarios building and analysis
Keywords in English
macroeconomic data
scenarios and complexity
self-organizing neural networks
Abstract in English
This study turns on an inquiry of viability of the use of self-organizing neural nets in classification and exploration of macroeconomic data. For this purpose, a method in which had been used self-organized neural topologies was elaborated, looking to explore the better characteristics of performance of each one of the models, under a sequential approach and with objective of acquiring intermediate knowledge in each one of its phases, diminishing the impact of the complexity as in time consuming as in analysis of results. Main results obtained suggest the use of self-organized artificial neural nets in acquisition of knowledge on Economic databases presents analog performance to traditional parametric models in scenarios building.
 
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MauriloBenite.pdf (637.16 Kbytes)
Publishing Date
2003-12-09
 
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