改进GM(1,1)模型在管道结蜡厚度预测中的应用研究

Application of an improved GM(1,1)model to predicting the wax deposition thickness of the pipelines to be adopted

为了准确预测含蜡原油管道的结蜡厚度,构建了基于灰色系统理论的改进GM(1,1)模型。在分析GM(1,1)模型基本原理和建模步骤的基础上,基于平移变换的思想建立了改进GM(1,1)模型,对比分析了改进GM(1,1)模型和传统GM(1,1)模型预测结果的差异,探讨了不同平移量对改进GM(1,1)模型拟合精度和预测精度的影响。结果表明:改进GM(1,1)模型的拟合精度和预测精度均高于传统GM(1,1)模型;随着平移量的增加,改进GM(1,1)模型的预测精度出现了先高后低的变化趋势,因此在实际应用中应对平移量进行合理选择;应用改进GM(1,1)模型来提高管道结蜡厚度的预测精度是可行的,具有一定的推广应用价值。

The paper is inclined to build up an improved GM(1,1)model based on the grey system theory so as to predict accurately the wax deposition thickness of the waxy crude oil pipeline.The original data series in this way have been processed with the method of transfer transformation and then on the basis of accumulating generating operation once of the new data series and calculating the adjacent neighbor mean generation sequence,the parameter series of the model have been gained through the least square estimation and the time response formula of the improved GM(1,1)model have also been gained.Based on the improved GM(1,1)model and taking the wax deposition thickness data of the indoor experiment(case 1)and the actual pipeline(case 2)as examples,we have verified the reliability of the improved GM(1,1)model and analyzed the influence of the different translation amounts on the fitting accuracy and prediction accuracy of the improved GM(1,1)model.Our research results of sample 1 show that the maximum relative error(which can be controlled in the range of 5%)between the calculated value and the experimental value of the improved GM(1,1)model can be made below that of the traditional GM(1,1)model(the maximum relative error is 9.091%).At the same time,the average relative error between the calculated value and the experimental one of the improved GM(1,1)model can also be made even lower than that of the traditional GM(1,1)one,so that the fitting accuracy of the improved GM(1,1)model can be made still higher.What is more,the prediction accuracy of the improved GM(1,1)model can be made further higher than that of the traditional GM(1,1)one.Nevertheless,with the increase of the translation amounts,the prediction accuracy of the improved GM(1,1)model may tend to reveal a trend of increase first and decrease later.And,in contrast,the research results of sample 2 tend to indicate that the fitting accuracy and the prediction accuracy of the improved GM(1,1)model can be made much higher than those of the traditional GM(1,1)model,with the changing trend of the prediction accuracy varying with the translation amounts,which turns out to be consistent with the results of case1.And,in general,different translation amounts may still affect the prediction accuracy of the model,which should be reasonably chosen in practical applications.Thus,it can be seen that the improved GM(1,1)model should be feasible and a certain practical application value for the prediction accuracy in heightening the wax deposition thickness of the pipeline.