基于灰色马尔柯夫链模型的浙江省名优茶产量预测

Yield Prediction of Famous Green Tea in Zhejiang Province Based on Grey-Markov Chain Theory

将灰色系统理论与马尔柯夫链结合在一起,建立了灰色-马尔科夫模型,并以此模型来对浙江省名优茶年产量进行预测,以达到科学指导生产、规划销售的目的。首先根据2000-2010年浙江省名优茶产量的统计资料,建立灰色系统GM(1,1)预测模型,并在此基础上运用马尔柯夫链理论对预测结果进行修正,得出更精确的预测结果。实例计算后发现,运用灰色马尔柯夫模型得到的预测结果较之单纯的GM(1,1)模型准确性有较大程度的提高。结果表明,灰色马尔柯夫模型更适用于对随机波动性较大的数列进行预测,此方法用于名优茶产量的预测是可行的。

In this paper , based on the combination of grey system theory and Markov chain theory , the grey Markov mod-el is established to forecast the yield of famous tea in Zhejiang Province .Firstly we build a dynamic GM （ 1 ,1 ） model ac-cording to the yield of famous tea in Zhejiang Province from 2000 to 2010 to obtain the evolution trend and predominant value of the famous-tea yield .Then the prediction result is modified by the use of Markov chain theory .The studied re-sults showed that the relative errors of predicted yield of grey Markov are much smaller .It shows that the forcasted results of the grey Markov model are more precise than the GM （ 1 ,1 ） model for data sequences with heavy random fluctuation . Using this grey Markov model to forcast the yield of famous tea in Zhejiang Province is feasible .