Use Model Of Box-Jenkins Method Estimate And Study The Aging Of The Glass Fiber Reinforced Plastics

In this article, Box-Jenkins Method is applied to forecast the aging of the glass fiber reinforced plastics. Box-Jenkins method, called B-J method or ARMA method, is a kind of time series forecast method which is named after American statistician George E.P.Box and British statistician Gwilym M.Jenkins. The method mainly attempts to solve the two following problems: One is to analyze the randomness, stability and seasonal characteristic of the time series;two is how to choose the appropriate model to carry on the forecast on the basis of the analysis of the time series. Its forecast models can be divided into: Auto Regression model (called the AR model), the moving average model (called the MA model) and the Auto Regression Integrated with Moving Averages (called the ARMA model).The basic idea of the Box-Jenkins Method is that the data series which is formed along with the time lapse by the forecasting objects is regarded as a random series, that is to say, if some individual adventitious observed value which is caused by accidental factors is removed, the time series will be a group of random variable rely on the time t.The dependence relationship or autocorrelation of this set of random variables has attributed the continuous nature of the forecasting object's development, and once this kind of autocorrelation is described by the corresponding mathematical model, the time series' past value and present value can be applied to forecast its future value. It can be made out that the Box - Jenkins Method is based on the time series autocorrelation analysis. The forecasting goal of this article is to obtain the aging series of glass fiber reinforced plastics. The aging forecast of the glass fiber reinforced plastics hasn't reported in domestic. The glass fiber can be used well as one kind of military and the industry material, so grasping its aged progress will help us use it better. The approximate frame is listed as follow: 1. The time series analysis is specifically introduced firstly. Only when we clearly grasped the time series analysis, can we have the possibility to carry on the further research. 2. The model. Box Jenkins Method which is mainly used in this forecast is introduced. 3. Real diagnosis forecast. 4. Finally the full text is generalized, the conclusion is drawn, andthe future research is proposed.