CAJ | 학술논문

通过时间序列分析可对传染病的发生、发展进行及时准确地预测预警,对有效防治传染病具有重要意义.该文在分析时间序列分析特点的基础上,就其中精度较高的差分自回归移动平均模型(auto regressive integrated moving average model,ARMIA)的分类和建模过程及其在寄生虫病等传染病预测中的应用等方面进行阐述,以为科研与防治工作者提供参考.
통과시간서렬분석가대전염병적발생、발전진행급시준학지예측예경,대유효방치전염병구유중요의의.해문재분석시간서렬분석특점적기출상,취기중정도교고적차분자회귀이동평균모형(auto regressive integrated moving average model,ARMIA)적분류화건모과정급기재기생충병등전염병예측중적응용등방면진행천술,이위과연여방치공작자제공삼고.
It is greatly valuable for prevention and control of infectious diseases by predicting and early warning their occurrence and tendency through time-series analysis.On the basis of analysing the characteristic of time-series method,an overview was conducted for auto regressive integrated moving average model (ARIMA model),one accurate predicting model,which covered its classification,modeling process and application in forecasting of infectious diseases,thus to provide reference for scientists and diseases control staffs.