Combining SOM and fuzzy rule base for sale forecasting in printed circuit board industry

  • Authors:
  • Pei-Chann Chang;K. Robert Lai

  • Affiliations:
  • Department of Industrial Engineering and Management, Yuan-Ze University, Nei-Li, Tao Yuan, Taiwan, China;Department of Computer Science & Engineering, Yuan-Ze University, Nei-Li, Tao Yuan, Taiwan, China

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
  • Year:
  • 2005

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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.