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目前统计部门对于当年粮食产量的预测,一般采用收获前抽样估计的方法,效果较好。但对于未来若干年的粮食产量的预测,还没有一个较好的办法。对粮食产量的长期预测,过去多采用多元回归预测法,但由于影响粮食产量的因素较多,使得多元回归方法具有很大的局限性,因而预报不够准确。本文力图克服这种局限,应用马尔柯夫理论对粮食产量进行预测,以求得到一个新的较准确的预测方法。
At present, statistical departments for the current forecast of food production, the general method of sampling before harvest, the effect is better. However, there is not a better way to predict food production in the coming years. In the long run, the multiple regression prediction method is used in the long-term prediction of grain yield. However, the multiple regression method has many limitations because of the many factors that affect the grain yield, so the prediction is not accurate enough. This paper seeks to overcome this limitation, the application of Markov theory forecast grain yield, in order to get a new more accurate prediction method.