Time Series Forecasting Using Hybrid ARIMA and ANN Models Based on DWT Decomposition

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Summary

A novel technique of forecasting by segregating a time series dataset into linear and nonlinear components through DWT is suggested, which achieves best forecasting accuracies for each series.

Type
article
Published
2015-01-01
Cited by
270
References
19
Access
Open access

Keywords

Autoregressive integrated moving average, Computer science, Series (stratigraphy), Discrete wavelet transform, Artificial neural network

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