An Artificial Neural Network (ANN) Model for Predicting Water Absorption of Nanoclay-Epoxy Composites

Journals Menu

Follow SCIRP

ISSN Print: 2327-6045
ISSN Online: 2327-6053
www.scirp.org/journal/msce
E-mail: msce@scirp.org

"An Artificial Neural Network (ANN) Model for Predicting Water Absorption of Nanoclay-Epoxy Composites"
written by Guillermina Capiel, Arrosio Florencia, Vera A. Alvarez, Pablo E. Montemartini, Juan Morán,
published by Journal of Materials Science and Chemical Engineering, Vol.7 No.8, 2019

has been cited by the following article(s):

[1]	Water absorption and leaching of a 1K structural model epoxy adhesive for the automotive industry
	Kregl… - Polymer Testing, 2023

[2]	Artificial neural networks for predicting potentiodynamic tests of brass 70-30
	Alvarez… - Materials Today …, 2023

[3]	Durability prediction of glass/epoxy composite using artificial neural network
	2022 Advances in Science …, 2022

[1]	ANN based prediction of the absorption characteristics of additive manufactured glycol‐modified polyethylene terephthalate nanocomposites reinforced with short‐carbon fibers and nanoclay fillers Polymer Composites, 2023 DOI:10.1002/pc.27337

[2]	Using machine learning to predict the long-term performance of fibre-reinforced polymer structures: A state-of-the-art review Construction and Building Materials, 2023 DOI:10.1016/j.conbuildmat.2023.133692

[3]	Durability prediction of glass/epoxy composite using artificial neural network 2022 Advances in Science and Engineering Technology International Conferences (ASET), 2022 DOI:10.1109/ASET53988.2022.9735032

Follow SCIRP