01718nas a2200181   4500008004100000245011700041210006900158260000900227300001400236490000700250520104700257653002201304653002201326653002301348653003501371100001301406856011701419       2013                        eng d00aAlgorithm research for supply chain demand prediction - Taking fresh agricultural product enterprises as example0 aAlgorithm research for supply chain demand prediction Taking fre  c2013  a160 - 1640 v113 aSupply chain demand prediction plays a very important role for enterprises to realize sales and markets management target effectively, especially for fresh agricultural product enterprises. A new model for supply chain demand prediction for fresh agricultural product enterprises is presented based on improved BP neural network. First the advantages and disadvantages of BP neural network algorithm are analyzed when it is used in supply chain demand prediction; Second, Legendre wavelets algorithm is used to speed up the convergence and improve the prediction accuracy of original BP neural network algorithm and based on this the paper advances a new supply chain demand prediction model for fresh agricultural product enterprises. Finally, certain fresh agricultural product enterprise is taken for example to verify the validity and feasibility of the model and the experimental results show that the model can improve prediction accuracy and decrease the calculation time and can be used for supply chain demand prediction practically.10aBP Neural Network10aLegendre wavelets10aMarkets management10aSupply chain demand prediction1 aWang, H.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84879120765&partnerID=40&md5=78a05f213a7f4f86b41f6e014b4c897b