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灰色自回归模型（ＧＡＲ）是将灰色系统模型（ＧＭ）与自回归模型（ＡＲ）结合起来的一类预测模型，它弥补了ＧＭ与ＡＲ的不足。本文叙述了该模型的建模方法，建立了江西省临川县１９６２～１９８７年稻瘟病年发病程度的ＧＡＲ模型，检验合格后，对该县的稻瘟病发生程度进行了多年预测（１９８８～１９９２）。运用模糊集合隶属函数对这几年的预测准确性进行评定，结果表明预测较为准确。文末还就ＧＡＲ模型用于稻瘟病预测的条件和特点进行了讨论。
The gray autoregressive model (GAR) is a type of forecasting model that combines the gray system model (GM) with the autoregressive model (AR) to make up for the deficiencies of GM and AR. This paper describes the modeling method of this model and establishes the GAR model of the annual incidence of rice blast in Linchuan County, Jiangxi Province from 1962 to 1987. After passing the test, the degree of rice blast occurrence in this county has been predicted for many years (1988 ~ 1992 ). The fuzzy set membership function is used to evaluate the prediction accuracy of these years, and the result shows that the prediction is more accurate. The article also discussed the conditions and characteristics of GAR model for rice blast prediction.