Muhamad, Noor Shahifah and Mohamed Din, Aniza (2015) Exponential smoothing techniques on time series river water level data. In: 5th International Conference on Computing and Informatics (ICOCI) 2015, 11-13 August 2015, Istanbul, Turkey.

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Abstract

The increasing of river water level usually happens during raining season.This event can lead to devastating flash flood, which would eventually cause damage to properties and possibly, loss of human life.Such event is also known as extreme event due to the nature of the data produced, which mostly consist of non linear pattern of data.The existence of nonlinear pattern and noise data greatly affect the quality of prediction result.Three exponential smoothing techniques have been investigated to study their ability in handling extreme river water level time series data, which are Single Exponential Smoothing Technique, Double Exponential Smoothing Technique and Holt’s Method.The techniques were performed on river water level data from three rivers in Perlis, Malaysia.From the experiments, it was found that all the three techniques have their own limitations in handling extreme data, with Double Exponential Smoothing Technique to perform better than its counterpart.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	ISBN No: 978-967-0910-02-4 Jointly organized by: Universiti Utara Malaysia & Istanbul Zaim University
Uncontrolled Keywords:	extreme event, extreme data, exponential smoothing technique, Holt’s method
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Business Management
Depositing User:	Mrs. Aniza Mohamed Din
Date Deposited:	12 Oct 2015 08:04
Last Modified:	27 Apr 2016 07:18
URI:	https://repo.uum.edu.my/id/eprint/15647

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