深度学习
计算力学
人工智能
计算机科学
相似性(几何)
人工神经网络
卷积神经网络
门派
物理
哲学
热力学
有限元法
图像(数学)
神学
作者
Genki YAGAWA,Atsuya Oishi
出处
期刊:Lecture notes on numerical methods in engineering and sciences
日期:2021-01-01
卷期号:: 199-208
被引量:3
标识
DOI:10.1007/978-3-030-66111-3_16
摘要
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 neural networks are reviewed (Sect. 16.1), then the applications of deep learning to the computational mechanics are shown (Sect. 16.2 for the applications of deep convolutional networks, and Sect. 16.3 for those of deep feedforward networks). Finally, the applications of miscellaneous deep networks to computational mechanics are discussed in Sect. 16.4.
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