中国农业气象

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基于马尔柯夫过程和概率分布特征的粮食产量预测

姜会飞;廖树华;丁谊;郭勇;   

  1. 中国农业大学资源与环境学院,中国农业大学资源与环境学院,中国农业大学资源与环境学院,中国农业大学资源与环境学院 北京100094,北京100094,北京100094,北京100094
  • 出版日期:2006-08-10 发布日期:2006-08-10
  • 基金资助:
    国家“十五”科技攻关项目(2001BA513B3-1)

Grain Crop Yield Prediction Based on Markov Model and Probability Distribution Character of Stochastic Series

JIANG Hui-fei,LIAO Shu-hua,DING Yi,Guo Yong(College of Resources and Environment,China Agricultural University,Beijing 100094,China)   

  • Online:2006-08-10 Published:2006-08-10

摘要: 通过分析粮食单产中气象产量分量时间序列的变化规律,综合运用马尔柯夫模型和概率密度分布函数,构建相对气象产量预测模型。以河南省民权县和陕西省武功县1949-1999年小麦单产序列为例构建模型,预测得到2000年两地区小麦产量的相对误差在20%以下。预测结果表明:综合运用马尔柯夫过程和概率分布特征预测粮食产量的方法是有效的。

关键词: 相对气象产量, 马尔柯夫模型, 概率分布, 粮食产量

Abstract: Based on Markov Model and probability distribution function,a relative meteorological yield prediction model of wheat was developed by analyzing the inter-annual time series variations of meteorological component of crop yield which was determined by the meteorological factors.The validation of the model was performed by using the wheat yields collected from Mingquan County in Henan Province and Wugong County in Shaanxi Province for the periods of 1949-1999.The simulation results showed that an accuracy of 81.6% and 88.6% had be respectively achieved for the two counties in the prediction of wheat yields for the year of 2000.It was indicated that the model was applicable to predict the crop yield.

Key words: Relative meteorological yield, Relative meteorological yield, Markov Model, Probability distribution, Grain crop yield