ID | 14795 |
Eprint ID | 14795
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フルテキストURL | |
著者 |
Hanaa, E.Sayed
Department of Systems Engineering, Division of Industrial Innovation Science, Okayama University
Hossam, A.Gabbar
Faculty of Energy Systems and Nuclear Science, UOIT
Soheir, A. Fouadc
Computer Science & Systems Engineering Department, Alexandria University
Khalil, M. Ahmedc
Computer Science & Systems Engineering Department, Alexandria University
Miyazaki, Shigeji
Department of Systems Engineering, Division of Industrial Innovation Science, Okayama University
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抄録 | Nowadays forecasting is needed in many fields such as weather forecasting, population estimation, industry demand forecasting, and many others. As complexity and factors increase, it becomes impossible for a human being to do the prediction operation without support of computer
system. A Decision support system is needed to model all demand factors and combine with expert opinions to enhance forecasting accuracy. In this research work, we present a decision support system using winters’, simple exponential smoothing, and regression statistical analysis with a new proposed genetic algorithm to generate operational forecast. A case study is presented using real industrial demand data from different products types to show the improved demand forecasting accuracy for the proposed system over individual statistical techniques for all time series types.
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キーワード | Forecasting
Genetic Algorithm
Regression Analysis
Support System
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発行日 | 2008-12
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出版物タイトル |
Proceedings : Fourth International Workshop on Computational Intelligence & Applications
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巻 | 2008巻
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号 | 1号
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出版者 | IEEE SMC Hiroshima Chapter
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開始ページ | 59
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終了ページ | 64
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資料タイプ |
会議発表論文
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言語 |
英語
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イベント | Fourth International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2008
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イベント地 | 東広島市
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イベント地の別言語 | Higashi-Hiroshima City
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論文のバージョン | publisher
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査読 |
有り
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Eprints Journal Name | IWCIA
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