PERFORMANCE OF 4253HT SMOOTHER BY DIFFERENT HANNINGS: APPLICATION IN RAINFALL DATA

Adie Safian  Ton Mohamed; Noor Izyan Mohamad Adnan; Qasim  Nasir Husain; Adina Najwa Kamarudin; Nurul Nisa’  Khairol Azmi

doi:10.11113/jurnalteknologi.v85.19720

Authors

Adie Safian Ton Mohamed School of Mathematics, Actuarial and Quantitative Studies, Asia Pacific University of Technology and Innovation, 57000 Kuala Lumpur, Malaysia
Noor Izyan Mohamad Adnan College of Computing, Informatics and Media, University Teknologi MARA Pahang, Jengka Campus, 26400 Jengka, Pahang, Malaysia
Qasim Nasir Husain Department of Mathematics, College of Education for Pure Science, Tikrit University, Iraq
Adina Najwa Kamarudin Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia https://orcid.org/0000-0001-7820-3922
Nurul Nisa’ Khairol Azmi College of Computing, Informatics and Media, University Teknologi MARA Negeri Sembilan, Seremban Campus, 70300 Seremban, Negeri Sembilan, Malaysia

DOI:

https://doi.org/10.11113/jurnalteknologi.v85.19720

Keywords:

Nonlinear smoother, 4253HT, extreme data, rainfall, noise

Abstract

Smoothing is an exploratory data analysis approach that focuses on removing noise or unstructured pattern from data series. This study mainly aims to compare the performance of 4253HT smoother in three types of Hannings and its application in forecasting. A sinusoidal signal was used where five different levels of contaminated normal noise were applied. Overall, 4253HT smoother with Shitan and Vazifean’s Hanning performs excellently over different percentages of noise, good at preserving edges, and able to travel closely with the signal of original pattern. The smoothed rainfall data gives a lower value of RMSE than the raw data which is 12.85 and 24.25 respectively. This concludes that the trend line obtained using smoothed data is more appropriate and reliable for forecasting. These results will be useful in predicting any time series data.

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