Hybrid wavelet model for time series prediction

Autor:	Luiz Albino Teixeira Junior, Cassius Tadeu Scarpin, Eliete Nascimento Pereira
Rok vydání:	2015
Předmět:	Wavelet Wavelet decomposition Exchange rate Artificial neural network Series (mathematics) Computer science Applied Mathematics Multilayer perceptron Econometrics Autoregressive integrated moving average Time series Algorithm Physics::Atmospheric and Oceanic Physics
Zdroj:	Applied Mathematical Sciences. 9:7431-7438
ISSN:	1314-7552
Popis:	To improve time series forecasts the wavelet decomposition has been applied. The combination of forecasting methods as the Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks have been used to achieve a higher quality time series forecasting than. This paper proposed a hybrid model composed of wavelet decomposition, ARIMA and neural network Multilayer Perceptron. These models are combined linearly then yielding the time series forecasting. The series studied are the Wolf's sunspots and the British pound/US dollar exchange rate data. The comparison of the proposed model in this paper with literature indicated an effective way to improve forecasting.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1ddd290944178902bcd537884b31f96b https://doi.org/10.12988/ams.2015.510628 Zobrazit plný text záznamu