Long-Term Prediction of Crack Growth Using Deep Recurrent Neural Networks and Nonlinear Regression: A Comparison Study

Long-Term Prediction of Crack Growth Using Deep Recurrent Neural Networks and Nonlinear Regression: A Comparison Study

Cracks in a building can potentially result in financial and life losses. Thus, it is essential to predict when the crack growth is reaching a certain threshold, to prevent possible disaster. However, long-term prediction of the crack growth in newly built facilities or existing facilities with rece...

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Bibliographic Details
Main Authors: Salahuddin Muhammad Iqbal, Jun-Ryeol Park, Kyu-Il Jung, Jun-Seoung Lee, Dae-Ki Kang
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
deep recurrent neural networks
LSTM
Seq2Seq LSTM
segmented nonlinear regression
long-term prediction
crack growth
Online Access:https://www.mdpi.com/2076-3417/12/20/10514

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https://www.mdpi.com/2076-3417/12/20/10514

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