Predictive modeling of nonlinear system responses using the residual improvement deep learning algorithm (RIDLA)

DOI10.1007/S00707-024-04095-7MaRDI QIDQ6661867

Kun Liu, Naijian Gu, Wenhua Wu, Xinglin Guo

Publication date: 13 January 2025

Published in: Acta Mechanica (Search for Journal in Brave)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computational methods for problems pertaining to mechanics of particles and systems (70-08) Random vibrations in mechanics of particles and systems (70L05)

Cites Work

• Title not available (Why is that?)
• A loading fractal prediction model developed for dry-friction rough joint surfaces considering elastic-plastic contact
• Nonlinear black-box modeling in system identification: A unified overview
• Surrogate modeling of elasto-plastic problems via long short-term memory neural networks and proper orthogonal decomposition
• A dual criterion of stochastic linearization method for multi-degree-of-freedom systems subjected to random excitation
• Finite Element Analysis

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