Хорижий лингвистика ва лингводидактика Volume 3 Issue 7 (2025) · pp. 80-92
Hybrid Waveform Diagnostics of Seasonal Time Series Models and Exponential Smoothing with the Application
Matkarimov, Akramjon, Маткаримов, Акрамжон, Matkarimov, Akramjon
Abstract
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.
Time seriesexponential smoothingwaveletshybrid model
Metadata source: the journal's OAI-PMH archive · Sindex does not store the full text; it links to the source.