MODELOS HÍBRIDOS AUTOREGRESSIVO-NEURAIS PARA SÉRIES TEMPORAIS / AUTOREGRESSIVE-NEURAL HYBRID MODELS FOR TIME SERIES

AUTOR(ES)

MARCELO TOURASSE NASSIM MELLEM

DATA DE PUBLICAÇÃO

1997

RESUMO

In this thesis we develop a piece-wise linear model named ARN model. Our model has a hybrid structure which combines autoregressive models and neural networks. We compare our model to the fixed-coefficient AR model and to the prediction static neural network. Our results show that ARN is able to find the non-linear structure of simulated data and in most cases it performs better than the methods mentioned above.

ASSUNTO(S)

series temporais time series

Documentos Relacionados

• Transformações em modelos de séries temporais
• Modelos lineares generalizadas para series temporais com memoria longa
• Stochastic models with heteroscedasticity for time series in finance
• A LINEAR-NEURAL HYBRID MODEL FOR ANALYSIS AND FORECASTING OF TIME-SERIES
• Recurrent neural networks for prediction of short and long memory time series