Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model

The goal of this research is to determine the forecasting performance of denoising signal. Monthly rainfall and monthly number of raindays with duration of 20 years (1990-2009) from Bayan Lepas station are utilized as the case study. The Fast Fourier Transform (FFT) and Wavelet Transform (WT) are us...

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Main Authors: Ismail, M.T., Mamat, S.S., Hamzah, F.M., Karim, S.A.A.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.32314 /
Published: American Institute of Physics Inc. 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904601016&doi=10.1063%2f1.4887720&partnerID=40&md5=3ee6487d62dae5da402a280d4bf708a8
http://eprints.utp.edu.my/32314/
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spelling utp-eprints.323142022-03-29T05:03:46Z Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model Ismail, M.T. Mamat, S.S. Hamzah, F.M. Karim, S.A.A. The goal of this research is to determine the forecasting performance of denoising signal. Monthly rainfall and monthly number of raindays with duration of 20 years (1990-2009) from Bayan Lepas station are utilized as the case study. The Fast Fourier Transform (FFT) and Wavelet Transform (WT) are used in this research to find the denoise signal. The denoise data obtained by Fast Fourier Transform and Wavelet Transform are being analyze by seasonal ARIMA model. The best fitted model is determined by the minimum value of MSE. The result indicates that Wavelet Transform is an effective method in denoising the monthly rainfall and number of rain days signals compared to Fast Fourier Transform. © 2014 AIP Publishing LLC. American Institute of Physics Inc. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904601016&doi=10.1063%2f1.4887720&partnerID=40&md5=3ee6487d62dae5da402a280d4bf708a8 Ismail, M.T. and Mamat, S.S. and Hamzah, F.M. and Karim, S.A.A. (2014) Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model. In: UNSPECIFIED. http://eprints.utp.edu.my/32314/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description The goal of this research is to determine the forecasting performance of denoising signal. Monthly rainfall and monthly number of raindays with duration of 20 years (1990-2009) from Bayan Lepas station are utilized as the case study. The Fast Fourier Transform (FFT) and Wavelet Transform (WT) are used in this research to find the denoise signal. The denoise data obtained by Fast Fourier Transform and Wavelet Transform are being analyze by seasonal ARIMA model. The best fitted model is determined by the minimum value of MSE. The result indicates that Wavelet Transform is an effective method in denoising the monthly rainfall and number of rain days signals compared to Fast Fourier Transform. © 2014 AIP Publishing LLC.
format Conference or Workshop Item
author Ismail, M.T.
Mamat, S.S.
Hamzah, F.M.
Karim, S.A.A.
spellingShingle Ismail, M.T.
Mamat, S.S.
Hamzah, F.M.
Karim, S.A.A.
Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model
author_sort Ismail, M.T.
title Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model
title_short Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model
title_full Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model
title_fullStr Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model
title_full_unstemmed Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model
title_sort forecasting performance of denoising signal by wavelet and fourier transforms using sarima model
publisher American Institute of Physics Inc.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904601016&doi=10.1063%2f1.4887720&partnerID=40&md5=3ee6487d62dae5da402a280d4bf708a8
http://eprints.utp.edu.my/32314/
_version_ 1741197716392771584
score 11.62408

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