摘要
[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 Province5 s straw resource5 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 rural employ population, crop sown area, consumption of chemical fertilizers and total power of agricultural machinery as four major factors afect- ing collectable amount of crop straw. GM (1,1) gray model a d multiple regression model based able amount of crop straw in Shaanxi from 2016 to 2020, using SAS. [Result]The prediction accuracy (1,1) was higher than GM (1,1) prediction. It accurately predicted the collectable amount of crop straw in Sh a an i Province from 2016 to 2020.[Conclusion ] The reliable prediction of crop straw^ollectable amount in Shaani provides a strong data support for control of agricultural surface pollution and improving the comprehensive utilization of straw for the governm
出处
《安徽农业科学》
CAS
2018年第6期186-189,共4页
Journal of Anhui Agricultural Sciences
关键词
陕西
秸秆
可收集量
灰色预测
SAS模型
Shaanxi
Crop straw
Collectable amount
Gray prediction
SAS model