农业工程学报2011，Vol.27Issue(12)：223-226,4.DOI:10.3969/j.issn.1002-6819.2011.12.042
基于灰色模型和ARMA模型的猪瘟月新发生次数预测比较
Comparison of grey model and ARMA model for predicting the number of monthly new outbreaks of CSF
摘要
Abstract
The quantitative prediction of the number of monthly new outbreaks of CSF can provide animal disease prevention and control departments the basis for taking selective preventive measures. Grey model and ARMA model were chosen to predict the number of monthly new outbreaks of CSF in Guizhou province, China. By grey model and ARMA model, outbreaks of CSF in Guizhou province were predicted according to the statistical data from veterinary bulletin from 2005 to 2008, and both models were assessed by the statistical data in 2009. Mean absolute error of grey model and ARMA model was 1.84 and 1.48 respectively, while mean absolute percentage error of two models was 0.272 and 0.229. The results showed that the prediction precision of ARMA model was higher than grey model, and ARMA model was feasible and effective for the prediction of CSF outbreaks in Guizhou province, China.关键词
动物/疾病/模型/灰色模型/ARMA模型/预测/时间序列Key words
animals/ disease/ grey model/ models/ ARMA model/classic swine fever/ prediction/ time series分类
农业科技引用本文复制引用
栾培贤,肖建华,陈欣,徐强,王洪斌..基于灰色模型和ARMA模型的猪瘟月新发生次数预测比较[J].农业工程学报,2011,27(12):223-226,4.基金项目
哈尔滨技术创新专项基金(2007RFXXN004) （2007RFXXN004）
