Water Absorption Rate Prediction of PMMA and Its Composites Using BP Neural Network

Abstract

Referring to water absorption rate of poly (methyl methacrylate) (PMMA) and its composites is hard to obtain under some working conditions, BP neural network prediction model was constructed. Regarding water absorption rate predictions of exfoliated PMMA/MMT nanocomposites in 0.1 mol/L H2SO4 solution, 0.1 mol/L NaOH solution and deionized water respectively as examples, the applicability of model established in water absorption rate prediction of PMMA and its composites was researched. The results show that the relative errors between prediction value obtained from model established and actual value of water absorption rate of composites soaking 63min in three kinds of mediums are 1.50%, 0.47% and 1.04% respectively, prediction accuracy is higher than that (relative errors are 3.89%, 3.40% and 4.43% respectively) obtained from GM (1, 1) model obviously. BP neural network can be used to predict water absorption rate of PMMA and its composites