Abstract
A key to success for manufacturing company in the worldwide competition is to build a reliable and accurate forecasting model that can predict in time suitable items at sufficient quantity and adapt to an uncertain environment. This paper presents a novel approach by combining SOM and fuzzy rule base for sales forecasting. Independent variables related to sales’ variation are collected and fed into the SOM for classification. Then, corresponding fuzzy rule base is selected and applied for sales forecasting. Genetic process is further applied to fine-tune the composition of the rule base. Finally, using the simulated data, the effectiveness of the proposed method is shown by comparing with other approaches.
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© 2005 Springer-Verlag Berlin Heidelberg
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Chang, PC., Lai, K.R. (2005). Combining SOM and Fuzzy Rule Base for Sale Forecasting in Printed Circuit Board Industry. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_150
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DOI: https://doi.org/10.1007/11427469_150
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25914-5
Online ISBN: 978-3-540-32069-2
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