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1860799989909815296
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2021-09-27 03:33:38
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| eventvenue |
Virtual, Online
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| format |
Restricted Document
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| id |
8209
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| institution |
UniSZA
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| originalfilename |
4163-01-FH03-FIK-21-56567.pdf
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Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML
like Gecko) Chrome/93.0.4577.82 Safari/537.36
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oai_dc
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https://intelek.unisza.edu.my/intelek/pages/view.php?ref=8209
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| spelling |
8209 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=8209 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper application/pdf 6 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/93.0.4577.82 Safari/537.36 2021-09-27 03:33:38 4163-01-FH03-FIK-21-56567.pdf UniSZA Private Access Determination the smoothing constant that minimizes mean absolute error and mean square deviation Exponential smoothing technique has become one of the quantitative techniques are very important in forecasting. The accuracy of forecasting based on this method depends on a parameter called the smoothing constant. Selection of smoothing constant value becomes very crucial because in forecasting prosecuted forecasting error is minimal. This paper discusses the selection of the optimal smoothing constant value which minimizes the mean square error (MSE) and the mean absolute deviation (MAD). Trial and error method is used to determine the optimal value of the smoothing constant based on the two criterias (MSE and MAD). Based on the analysis carried out, there was no regularity of the relationship between the amount of data and the smoothing constant value that minimized MAD and MSE. 11th Annual International Conference on Industrial Engineering and Operations Management Virtual, Online
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| spellingShingle |
Determination the smoothing constant that minimizes mean absolute error and mean square deviation
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| summary |
Exponential smoothing technique has become one of the quantitative techniques are very important in forecasting. The accuracy of forecasting based on this method depends on a parameter called the smoothing constant. Selection of smoothing constant value becomes very crucial because in forecasting prosecuted forecasting error is minimal. This paper discusses the selection of the optimal smoothing constant value which minimizes the mean square error (MSE) and the mean absolute deviation (MAD). Trial and error method is used to determine the optimal value of the smoothing constant based on the two criterias (MSE and MAD). Based on the analysis carried out, there was no regularity of the relationship between the amount of data and the smoothing constant value that minimized MAD and MSE.
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| title |
Determination the smoothing constant that minimizes mean absolute error and mean square deviation
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| title_full |
Determination the smoothing constant that minimizes mean absolute error and mean square deviation
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| title_fullStr |
Determination the smoothing constant that minimizes mean absolute error and mean square deviation
|
| title_full_unstemmed |
Determination the smoothing constant that minimizes mean absolute error and mean square deviation
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| title_short |
Determination the smoothing constant that minimizes mean absolute error and mean square deviation
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| title_sort |
determination the smoothing constant that minimizes mean absolute error and mean square deviation
|