The study aims to evaluate the effectiveness of wavelet analysis as a diagnostic tool for univariate time series models by comparing several traditional and wavelet-based methods. It also seeks to compare the performance of two different approaches for analyzing and forecasting univariate time series: traditional exponential smoothing and wavelet analysis. Additionally, the research explores the effectiveness of a hybrid model combining exponential smoothing and wavelet filters. These methods were applied to real-world data, with results showing that the hybrid model achieves higher predictive accuracy and excels in isolating noise and abrupt changes.
| Mualliflar | Al-Haleem, Rusul Ali Abd, Hayawi, Heyam A. |
|---|---|
| Jurnal | Innovative Multidisciplinary Journal of Applied Technology |
| Nashr sanasi | 2025-07-30 |
| Jild | 3 |
| Son | 7 |
| Betlar | 80-92 |
| Til | Ingliz |
Time series, exponential smoothing, wavelets, hybrid model
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