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    ARTICLE

    Wavelet Decomposition Impacts on Traditional Forecasting Time Series Models

    W. A. Shaikh1,2,*, S. F. Shah2, S. M. Pandhiani3, M. A. Solangi2

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1517-1532, 2022, DOI:10.32604/cmes.2022.017822 - 30 December 2021

    Abstract This investigative study is focused on the impact of wavelet on traditional forecasting time-series models, which significantly shows the usage of wavelet algorithms. Wavelet Decomposition (WD) algorithm has been combined with various traditional forecasting time-series models, such as Least Square Support Vector Machine (LSSVM), Artificial Neural Network (ANN) and Multivariate Adaptive Regression Splines (MARS) and their effects are examined in terms of the statistical estimations. The WD has been used as a mathematical application in traditional forecast modelling to collect periodically measured parameters, which has yielded tremendous constructive outcomes. Further, it is observed that the More >

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