Long short-term memory for nonlinear static analysis of functionally graded plates
This study presents an effective method based on long short-term memory to reduce the computational cost in nonlinear static analysis of functionally graded plates. Data points representing a load-deflection curve in a dataset are generated through isogeometric analysis (IGA). The order of these data points is always maintained as a sequential series of observations; therefore, it is referred to as a time series. Dataset is divided into three sets including training, testing, and prediction sets. Both training and testing sets are used for the training process by the long short-term memory to gain optimum weights. Based on these obtained weights, data points in the prediction set are directly predicted without using any analysis tools. The effectiveness and accuracy of the proposed method are demonstrated by comparing the obtained results to those of isogeometric analysis.
Copyright (c) 2022 Hanoi University of Civil Engineering
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
1. The Author assigns all copyright in and to the article (the Work) to the Journal of Science and Technology in Civil Engineering (STCE Journal) – Hanoi University of Civil Engineering (HUCE), including the right to publish, republish, transmit, sell and distribute the Work in whole or in part in electronic and print editions of the Journal, in all media of expression now known or later developed.
2. By this assignment of copyright to the STCE Journal, reproduction, posting, transmission, distribution or other use of the Work in whole or in part in any medium by the Author requires a full citation to the Journal, suitable in form and content as follows: title of article, authors’ names, journal title, volume, issue, year, copyright owner as specified in the Journal, DOI number. Links to the final article published on the website of the Journal are encouraged.
3. The Author and the company/employer agree that any and all copies of the final published version of the Work or any part thereof distributed or posted by them in print or electronic format as permitted herein will include the notice of copyright as stipulated in the Journal and a full citation to the Journal as published on the website.