基于马尔克夫的灰色残差GM(11)模型在塑料老化行为预测中的应用

针对数据的离散程度较大时灰色GM(11)模型的预测精度较差这一问题引入残差修正在采用马尔克夫过程确定预测值的残差修正值正负号的基础上通过对灰色GM(11)模型得到的模拟值和预测值进行修正构建了基于马尔克夫的灰色残差GM(11)模型。以大气自然老化环境下LDPE棚模的拉伸强度的预测为例研究所建模型在塑料老化行为预测中的适用性。结果表明：由所建模型得到的LDPE棚模老化18个月和21个月的拉伸强度预测值与实际值的相对误差分别为1.49%和4.96%预测精度明显高于灰色GM(11)模型(相对误差分别为3.40% 和6.75%)可用于塑料老化行为的预测。马尔克夫的灰色残差GM(11)模型所需实验数据少预测精度高为塑料老化行为的预测提供了一种简易而可靠的新途径。

The application of grey residual error GM(11)model based on Markvo to aging behavior prediction of plastic

To solve the problem of poor prediction accuracy of GM(11)model when the data are discretebased on the sign of residual error modification value of prediction value being determined by Markvo chaina residual error modification is presented.The grey residual error GM(11)model based on Markvo is constructed through the modification of simulation value and prediction value obtained from GM(11)model.The prediction of tensile strength of LDPE greenhouse film under natural aging condition is taken as an exampleand the applicability of constructed model in the prediction of plastic aging behavior is researched.The results show that the relative error between prediction value and the actual value of tensile strength of LDPE greenhouse film after aging 18 and 21 months obtained from constructed model are 1.49% and 4.96% respectively.Prediction accuracy are higher than that(relative error are 3.40% and 6.75% respectively)obtained from GM(11)model obviously.Grey residual error GM(11)model based on Markvo needs less original data and has high prediction accuracythus it is a simple and reliable method for plastic aging behavior prediction.