Long short-term memory for nonlinear static analysis of functionally graded plates

نویسندگان

چکیده

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 dataset are generated through isogeometric (IGA). The order these data is always maintained as sequential series observations; therefore, it referred time series. Dataset divided into three sets including training, testing, and prediction sets. Both training testing used for process by gain optimum weights. Based obtained weights, set directly predicted without using any tools. effectiveness accuracy proposed demonstrated comparing results those analysis.

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ژورنال

عنوان ژورنال: T?p chí Khoa h?c Công ngh? Xây d?ng

سال: 2022

ISSN: ['2734-9489', '2615-9058']

DOI: https://doi.org/10.31814/stce.huce(nuce)2022-16(3)-01