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Prediction model of supply chain demand based on fuzzy neural network with chaotic time series

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3 Author(s)
Wang Xu ; Manage. Sci. & Eng., Northeast Forestry Univ., Harbin, China ; Jia Yan-min ; Li Hui

In order to quickly determine and control the chaotic oscillation in supply chain system, to enhance the prediction accuracy of supply chain demand, and ensure the stability of supply chain systems, using fuzzy neural networks based on chaotic time series, sub-phase space is rebuilt by the demand time-series of supply chain system. Calculating the phase-space saturated embedding dimension and the largest Lyapunov index. Prediction model of supply chain demand has been built by fuzzy neural network based on a chaotic time series. The chaotic phenomena has been judged in supply chain system. Supply chain demand prediction controller has been designed based on fuzzy neural network. The simulating results show that fuzzy neural network with chaotic time series is feasible and effective on prediction of supply chain demand.

Published in:

Service Operations, Logistics and Informatics, 2009. SOLI '09. IEEE/INFORMS International Conference on

Date of Conference:

22-24 July 2009