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ID 14795
Eprint ID
14795
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
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.
キーワード
Forecasting
Genetic Algorithm
Regression Analysis
Support System
発行日
2008-12
出版物タイトル
Proceedings : Fourth International Workshop on Computational Intelligence & Applications
2008巻
1号
出版者
IEEE SMC Hiroshima Chapter
開始ページ
59
終了ページ
64
資料タイプ
会議発表論文
言語
English
イベント
Fourth International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2008
イベント地
東広島市
イベント地の別言語
Higashi-Hiroshima City
論文のバージョン
publisher
査読
有り
Eprints Journal Name
IWCIA