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ID 14795
Eprint ID
14795
FullText URL
Author
Hanaa, E.Sayed
Hossam, A.Gabbar
Soheir, A. Fouadc
Khalil, M. Ahmedc
Miyazaki, Shigeji
Abstract
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.
Keywords
Forecasting
Genetic Algorithm
Regression Analysis
Support System
Published Date
2008-12
Publication Title
Proceedings : Fourth International Workshop on Computational Intelligence & Applications
Volume
volume2008
Issue
issue1
Publisher
IEEE SMC Hiroshima Chapter
Start Page
59
End Page
64
Content Type
Conference Paper
language
英語
Event Title
Fourth International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2008
Event Location
東広島市
Event Location Alternative
Higashi-Hiroshima City
File Version
publisher
Refereed
True
Eprints Journal Name
IWCIA