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《Journal of Anhui Agricultural Sciences》 2008-14
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ARMA Forecast Model of Tar of Cigarette Smoke

LU Ming et al(Technology Center of China Tobacco Fujian Industrial Corporation,Xiamen,Fujian 361022)  
[Objective] The study aimed to provide a base for computer-aided formula design.[Method] With the tar of cigarettes from different batches of cigarettes with the same trademark as tested materials and by using time series sequence method,the forecast model of tar of cigarette smoke was built and validated.[Result] Among forecast models,the values of AIC,LF and FPE were all least in ARMA(2,2)model,namely(1-1.622 q-1+0.844 q-2) y(t) =(1-1.836 q-1 + 1.02 q-2) e(t),so it was selected as forecast model for tar of cigarette smoke.The established ARMA(2,2)model was significantly effective model according to autocorrelation check of the residuals on the model residual sequence.The forecast precision of ARMA(2,2)model reached 99.51% and the average relative error was 0.49%,so the ARMA(2,2)model belonged to the first grade model(excellent model).However,time series model was usually used for short-term forecast but not for long-term forecast.[Conclusion] The forecast model of tar of cigarettes smoke built in this study had a better precision,lower error and could beused for short-term forecast of the tar of cigarettes smoke.
【CateGory Index】: TS411
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