Lashari, Saima Anwar and Ibrahim, Rosziati and Senan, Norhalina (2017) Exponential smoothing techniques on daily temperature level data. In: 6th International Conference on Computing & Informatics (ICOCI2017), 25 - 27 April 2017, Kuala Lumpur.

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Abstract

The changes of temperature level occur throughout the year.This event whether hot temperature or cold temperature can affect human life and nature. Such event is also known as extreme event due to the nature of the data produced.Usually the time series of extreme dataset is rarely linear.The existence of nonlinear pattern and high fluctuation in variation greatly affect the quality of forecasting performances.Three exponential smoothing techniques have been tested to study their ability in handling of temperature level data from three cities in Texas.Single Exponential Smoothing Technique (SEST), Double Exponential Smoothing Technique (DEST) and Holt’s method were explored in preparing the temperature data.From the experiments, it was found that DEST is the most suitable technique to deal with the data compared to SEST and Holt's method.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	EISSN 2289-7402 E-ISBN 978-967-0910-33-8 Organized by: School of Computing, Universiti Utara Malaysia
Uncontrolled Keywords:	temperature level, extreme event, extreme data, exponential smoothing technique
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	26 Jul 2017 07:39
Last Modified:	26 Jul 2017 07:39
URI:	https://repo.uum.edu.my/id/eprint/22797

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