MATEC Web Conf.
Volume 175, 20182018 International Forum on Construction, Aviation and Environmental Engineering-Internet of Things (IFCAE-IOT 2018)
|Number of page(s)||4|
|Section||Computer Simulation and Design|
|Published online||02 July 2018|
Prediction of Rubber Aging Life by Intelligent Neural Network
Electromechanic Engineering College, Beijing University of Chemical Technology, Chaoyang, Beijing, China
2 Shanghai Jingyi Rubber Technology Co., Ltd., Shanghai, China
Corresponding author: email@example.com
Predicting the agin life of rubber is mostly based on traditional dynamic methods. These methods often have some limitations, which can not reflect the influence of certain factors. To avoid such limitations, a BP neural network model was established to predict the aging life of rubber. Comparing with the BP neural network model, results from the genetic algorithm optimization model (GA-BP) and the particle swarm optimization model (PSO-BP) showed that the GA-BP network model has better stability and accuracy and can quickly get the global optimal solution. The prediction accuracy of the GA-BP neural network model is better than that of the traditional dynamic model and its result is in good agreement with the experimental data.
© The Authors, published by EDP Sciences 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.