[目的]在SAS环境下,运用灰色系统理论对陕西省农作物秸秆可收集量进行预测.[方法]以草谷比和可收集系数估算2005—2015年陕西省农作物秸秆可收集量.以农村就业人口、农作物播种面积、农用化肥施用量和农业机械总动力作为影响农作物秸秆可收集量的4个主要因素进行灰色关联度分析.在SAS环境下,利用GM(1,1)灰色模型和基于GM(1,1)的多元回归模型对2016-2020年的陕西农作物秸秆可收集量进行预测,并对模型精度与误差进行分析比较.[结果]基于GM(1,1)的多元回归模型预测精度高于GM(1,1)模型的精度,较准确预测了2016-2020年陕西农作物秸秆的可收集量.[结论]准确预测农作物秸秆可收集量可为政府开展农业面源污染防治、提高秸秆综合利用提供强有力的数据支撑.%[Objective] To predict Shaanxi Province' s straw resource' collectable amount based an SAS by using gray system theory.[Method]Collectable amount of straw resource from 2005 to 2015 was estimated based on the residue to grain ratio and collection coefficient.To analyze the rural employ population,crop sown area,consumption of chemical fertilizers and total power of agricultural machinery as four major factors affecting collectable amount of crop straw.GM (1,1) gray model and multiple regression model based on GM (1,1) were used to predict the collectable amount of crop straw in Shaanxi from 2016 to 2020,using SAS.[Result] The prediction accuracy of multiple regression model based on GM (1,1) was higher than GM (1,1) prediction.It accurately predicted the collectable amount of crop straw in Shaanxi Province from 2016 to 2020.[Conclusion] The reliable prediction of crop straw'collectable amount in Shaanxi provides a strong data support for carrying out the prevention and control of agricultural surface pollution and improving the comprehensive utilization of straw for the government.
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