This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine learning's fundamental concepts before neural networks are explained thoroughly
The rapid interest in machine learning in general and within computational mechanics is well documented in the scientific literature. By considering the number of publications treating “Artificial Intelligence”, “Machine Learning”, “Deep Learning”, and “Neural Networks”, the interest can be quan...
Since the deep learning is now a hot topic in computational mechanics with neural networks and many related studies have been reported recently, we discuss here some features of computational mechanics with deep learning. First, similarity and difference between conventional neural networks and deep neu...
Deep learning in computational mechanics: a review 2024, Computational Mechanics FLUID-GPT (Fast Learning to Understand and Investigate Dynamics with a Generative Pre-Trained Transformer): Efficient Predictions of Particle Trajectories and Erosion 2023, Industrial and Engineering Chemistry Research View all ...
近年来,深度学习技术在多个工程领域取得了显著突破,特别是在疲劳与断裂分析中的应用。传统的疲劳分析方法依赖于物理模型和实验数据,然而,随着结构复杂性的增加和多物理场交互的挑战,传统方法的计算成本和准确性已无法满足高精度要求。深度学习...
However, with the deep learning DFT Hamiltonian method available, the computational cost can be greatly reduced34 (also see Supplementary Section 5). As illustrated in Fig. 1d, the neural network trained on the reconstructed AO Hamiltonian manages to give very accurate predictions when compared with...
and the generated innumerable datasets resulted in complexities during analysis. The deep learning (DL) technique used in this study provides a good solution, as it can effectively learn the hidden patterns from a large number of datasets. The DL approach builds predictive models with multiple level...
That requires a lengthier discussion than if I just presented the basic mechanics of what's going on, but it's worth it for the deeper understanding you'll attain. Amongst the payoffs, by the end of the chapter we'll be in position to understand what deep learning is, and why it ...
Deep learning is an advanced form of machine learning that uses neural networks to “learn” from large amounts data. These artificial brains are designed in the shape and function similar as our own human brain
learning has led to rapid growth in algorithms and methods for solving a variety of ill-posed inverse computational imaging problems45, such as super-resolution microscopy46, lensless phase imaging47, computational ghost imaging48, and image through scattering media49. In this context, researchers in...