A Comparison between Brown’s and Holt’s Double Exponential Smoothing for Forecasting Applied Generation Electrical Energies in Kurdistan Region

  • Ameera W. Omer Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region - F.R. Iraq
  • Hazhar T. A. Blbas Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region - F.R. Iraq
  • Dler H. Kadir Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region, Iraq; (2) Department of Business Administration, Cihan University-Erbil, Iraq https://orcid.org/0000-0001-5196-4457
DOI: https://doi.org/10.24086/cuesj.v5n2y2021.pp56-63
Keywords: Generation electrical, Energies, double exponential smoothing parameter optimization, electricity production

Abstract

The process of producing electricity from sources of energy is known as electricity production. Electric also isn't freely accessible in environment, thus it should be "manufactured" (i.e., converting another kinds of energy to electrical energy) by utilities with in electricity industry (transportation, distributing, and so on).Moreover, the objective of this study is to compared of Brown’s as well as Holt’s Double Exponential Smoothing also build a best forecasting time series model among two smoothing model forecasting, as well as focuses on optimizing characteristics to use the golden section technique.  This exponential smoothing approach has been one of the time series forecasting methods that would be used to forecast (Generation Electrical) with in Kurdistan area. The issue that arises with this technique is determining the appropriate parameters to reduce predict inaccuracy. In addition, Data used in this paper are (Generation Electrical) in Kurdistan region for (132) months from 2010 to 2020. The study revealed that such data is trending modeled, indicating that a double exponential smoothing (DES) approach from Brown & Holt can be used with the (Stratigraphic & Minitab) software. There are the same results but the Result of analysis more depend on the R-program. The difference among the forecast findings acquired with optimum parameters as well as the assaying data was utilized to assess the feasibility of the forecast by completing normality and randomness tests. Ultimately, the outcomes of parameterization show that the optimal value of α that in DES Brown is (0.22) as well as the optimal MAPE is 9.23616 percent, whereas in DES Holt the optimal is (0.95) as well as the optimal β is (0.05) via the optimal MAPE of 8.08586 percent. This MAPE of a DES Brown technique is greater than the MAPE of a DES Holt approach. Feasibility experiments revealed that both approaches are capable of predicting. Depending on the value of MAPE as well as evaluation process, DES Holt's was recognized as the main prediction model.

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Author Biographies

Hazhar T. A. Blbas, Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region - F.R. Iraq

Hazhar Blbas is a lecturer in Statistics Department in College of Administration and Economics at Salahaddin University Erbil. He gained his bachelor degree in Statistics Department at Salahaddin University and he was the third student among 132 students with average 85.516 in 2007.  He gained master degree scholarship in Applied Statistics at University of Central Florida in the United States of America with GPA 3.425 out of 4 on May 2014. Now he is a PhD candidate in Statistics Department at Salahaddin University in the last year of his study

Dler H. Kadir, Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region, Iraq; (2) Department of Business Administration, Cihan University-Erbil, Iraq

Dler H. Kadir was awarded a B.Sc. in Statistics from the University of Salahaddin in 2002.  He also received an M.Sc. degree in applied statistics at Sulaymaniyah University in 2007. He was awarded a PhD from Sheffield University in 2018. His research interest includes; Bayesian inference, MCMC, Statistical Modeling, Quality control charts and Time series analysis

References

P. A. S. Dharmawan, and I. G. A. Indradewi. Double exponential smoothing brown method towards sales forecasting system with a linear and non-stationary data trend. Journal of Physics: Conference Series, vol. 1810, no. 1, p. 012026, 2021.

M. B. Hasan, and M. N. Dhali. Determination of optimal smoothing constants for exponential smoothing method and holt’s method. Dhaka University Journal of Science, vol. 65, no. 1, pp. 55-59, 2017.

F. Sidqi, and I. D. Sumitra. Forecasting product selling using single exponential smoothing and double exponential smoothing methods. IOP Conference Series: Materials Science and Engineering, vol. 662, p. 032031, 2019.

W. Anggraeni. Perbandingan metode fuzzy time series hsu dan double exponential smoothing pada peramalan nilai tukar rupiah terhadap dolar amerika. Jurnal Riset Manajemen dan Bisnis (JRMB) Fakultas Ekonomi UNIAT, vol. 1, no. 2, pp. 153-162, 2016.

Wikipedia Contributors, “Exponential smoothing,” Wikipedia, Feb. 21, 2019. https://en.wikipedia.org/wiki/Exponential_smoothing.

V. A. Fitria. Parameter optimization of single exponential smoothing using golden section method for groceries forecasting. ZERO: Jurnal Sains, Matematika dan Terapan, vol. 2, no. 2, p. 89, 2019.

A. N. Aimran, and A. Afthanorhan. A comparison between single exponential smoothing (SES), double exponential smoothing (DES), holts (brown) and adaptive response rate exponential smoothing (ARRES) techniques in forecasting Malaysia population. Global Journal of Mathematical Analysis, vol. 2, no. 4, p. 276, 2014.

F. Ikhsan. Forecasting of criminality problems using double exponential smoothing method. Academia Open, vol. 4, p. 122, 2021.

K. Aroian, N. Uddin, and H. Blbas. Longitudinal study of stress, social support, and depression in married Arab immigrant women. Health Care for Women International, vol. 38, no. 2, pp. 100-117, 2016.

R. Rachmat, and S. Suhartono. Comparative analysis of single exponential smoothing and holt’s method for quality of hospital services forecasting in general hospital. Bulletin of Computer Science and Electrical Engineering, vol. 1, no. 2, pp. 80-86, 2020.

Published
2021-11-30
How to Cite
1.
Omer A, Blbas H, Kadir D. A Comparison between Brown’s and Holt’s Double Exponential Smoothing for Forecasting Applied Generation Electrical Energies in Kurdistan Region. cuesj [Internet]. 30Nov.2021 [cited 23Apr.2024];5(2):56-3. Available from: https://journals.cihanuniversity.edu.iq/index.php/cuesj/article/view/522
Issue
Vol 5 No 2 (2021)
Section
Research Article

Copyright (c) 2021 Ameera W. Omer, Hazhar T. A. Blbas, Dler H. Kadir

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