Corpus ID: 55422222

SISTEMA HÍBRIDO EVOLUCIONÁRIO BASEADO EM DECOMPOSIÇÃO PARA PREVISÃO DE SÉRIES TEMPORAIS Por

@inproceedings{Fausto2016SISTEMAHE,
  title={SISTEMA HÍBRIDO EVOLUCIONÁRIO BASEADO EM DECOMPOSIÇÃO PARA PREVISÃO DE SÉRIES TEMPORAIS Por},
  author={Juliana Fausto and L. D. Oliveira and Tese de Doutorado and Jo{\~a}o Fausto Lorenzato and T. Ludermir and J. L. Alves and Nazareno CRB and Jorge Silva Valença},
  year={2016}
}
  • Juliana Fausto, L. D. Oliveira, +5 authors Jorge Silva Valença
  • Published 2016
  • Time series forecasting is an important task in the field of machine learning and has many applications in stock market, hydrology, weather and so on. The analysis of the dependence between adjacent observations in the series is necessary in order to achieve better forecasts. Dynamic models are used to perform mappings in the time series by approximating to the data generating process and being able to perform predictions. However, the data generating process of a time series may produce both… CONTINUE READING

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