MATEC Web Conf.
Volume 67, 2016International Symposium on Materials Application and Engineering (SMAE 2016)
|Number of page(s)||7|
|Section||Chapter 6 Materials Science|
|Published online||29 July 2016|
Water Absorption Rate Prediction of PMMA and Its Composites Using BP Neural Network
1 School of Bailie Engineering & Technology, Lanzhou City University, Lanzhou 730070, China
2 Center of Information and Network, Lanzhou City University, Lanzhou 730070, China
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.
Key words: PMMA poly (methyl methacrylate) / Water absorption rate / Prediction / BP neural network
© The Authors, published by EDP Sciences, 2016
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