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Application of time-series autoregressive integrated moving average model in predicting the epidemic situation of newcastle disease

机译:时间序列自回归综合移动平均模型在新城疫流行情况预测中的应用

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Objective: The outbreak of animal infectious diseases directly affects the economic benefits of livestock and poultry production, and even threatens the safety of human life. And due to the specificity of livestock and poultry production, the infectious diseases will be difficult to control by medical treatment means when outbreak in groups. Knowing the outbreak and development of infectious diseases as early as possible is the key to control the eradication of the epidemic. Nowadays, people have studied many methods for disease forecasting and early warning, and in this study, the mathematical model was established for predicting the occurrence of Newcastle disease, evaluation of mathematical model of animal disease on the accuracy of the forecasts. Method: The present study fitted an ARIMA model based on the monthly incidence of Newcastle disease collected from the Veterinary bulletin in two areas (A and B) from Jan. 2000 to Dec. 2007. The spss software was used to set up time series model which was applied to predict the incidence of Newcastle disease from Jan. to Dec. 2008 in above areas and validated by comparing with the actual incidence. Results: The result showed the predicted incidence of ARIMA model was consistent with the actual incidence of Newcastle disease, which indicated the constructed ARIMA model can be applied to predict the incidence of Newcastle disease so as to supply the reliable reference for this disease in future.
机译:目的:爆发动物传染病直接影响牲畜和家禽生产的经济效益,甚至威胁人类生命的安全性。由于牲畜和家禽生产的特异性,在爆发组中,通过医疗意味着感染性疾病将难以控制。尽早了解传染病的爆发和发展是控制消除流行病的关键。如今,人们已经研究了许多疾病预测和预警方法,并且在这项研究中,建立了数学模型,以预测新城疫的发生,动物疾病数学模型对预测的准确性的评估。方法:本研究根据2000年1月至12月从兽医公报中收集的新城疫每月发病率的ARIMA模型。SPSS软件用于设置时间序列模型这被应用于从1月到2008年12月在上述领域预测新城疫的发病率,并通过与实际发病率进行验证。结果表明,该结果表明,ARIMA模型的预测发生率与新城疫的实际发生率一致,这表明构建的ARIMA模型可用于预测新城疫的发病率,以便将来为该疾病提供可靠的参考。

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