Application of grey model and ARIM multiple seasonal model in the prediction of brucellosis in Chengde of Heibei Province
10.3760/cma.j.issn.2095-4255.2018.04.018
- VernacularTitle:灰色模型与ARIMA乘积季节模型在河北省承德市布鲁菌病预测中的应用
- Author:
Haikuo HE
1
;
Zhanhui WANG
Author Information
1. 河北省承德石油高等专科学校计算机系
- Keywords:
Grey model;
ARIMA model;
Brucellosis;
Prediction
- From:
Chinese Journal of Endemiology
2018;37(4):338-340
- CountryChina
- Language:Chinese
-
Abstract:
Objective The grey model [GM (1,1)] and the ARIMA multiple seasonal model were used to predict the incidence trend of brucellosis in Chengde,and the effects of predictions of the two models is compared.Methods According to the statistical results of epidemiological research results of monthly brucellosis patients in Chengde from 2008 to 2014,we established the ARIMA multiple seasonal model and GM (1,1) model,individually predicted the trend of brucellosis in 2015.Compared with the actual monitoring results,the average relative error was used to verify the reliability of the model.Results GM (1,1) model was (X)0(k) =0.001 6 (X)0 + 23 712.31) exp [0.001 6 (k-t0)],and the optimal model for determining the ARIMA multiple seasonal model of product was ARIMA (0,1,1) × (0,1,0)12.The average relative errors of the two models predicted in 2015 from January to December compared with the actual monitoring data were 114.82％ and 11.66％.Conclusion The product ARIMA multiple seasonal model has better predictive effect on brucellosis,and can be used for short-term forecasting.
