Prediction of wax deposition thickness on pipe wall by improved GM (1,1) model based on data transformation method

Abstract

The improved GM (1,1) models for predicting wax deposition thickness on the pipe wall under different deposition times were established by introducing the idea of square root transformation and logarithmic transformation into the modeling step of GM (1,1), the prediction accuracy of the established models and the traditional GM (1,1) modelwere compared and analyzed, and the influences of the change of constant C on the fitting and prediction accuracy of the model were discussed. The calculation results of different examples show that: After the square root transformation (improved model I) and logarithmic transformation (improved model II), the maximum relative errors between the fitting results of the improved models and the actual values are lower than those of the traditional model. The prediction results of the improved model are in good agreement with the actual values, and the prediction accuracy of the improved model is higher than that of the traditional model. The change of C value has an important impact on the prediction accuracy of the improved model, the increase of C value does not mean that the prediction accuracy of the improved model is higher, the reasonable C value can make the model have higher prediction accuracy.