Titlebook: Computational Mechanics with Neural Networks; Genki Yagawa,Atsuya Oishi Book 2021 The Editor(s) (if applicable) and The Author(s), under e

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Deep LearningChapter 3 deals with the deep learning based on the viewpoint that it is an extended version of the feedforward neural network. Section . describes what is common and what is different between the deep learning and the feedforward neural network. Techniques for pretraining are described in Sects. . and ..

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Mutually Connected Neural NetworksThis chapter focuses on the mutually connected neural networks. Section . describes the Hopfield network, and Sect. . the Boltzmann machine.

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Introductory RemarksThis chapter provides an introduction for the application of neural networks to computational mechanics, where a basic procedure is discussed to incorporate neural networks in computational mechanics.

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https://doi.org/10.1007/978-981-10-3824-2ork well as the neural networks. In addition, neural networks are often combined with other machine learning algorithms. This chapter describes several algorithms, which are often combined with or compared with neural networks, including the genetic algorithm (GA), the genetic programming (GP), the

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https://doi.org/10.1007/978-981-10-4475-5rical quadrature of the elemental integration. Chapter 9 deals with this issue: Section . describes the classification of the finite elements based on the convergence speed in numerical quadrature, and Sect. . the optimization of quadrature parameters.