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Akademický článek

Influence of the parameters of the convolutional neural network model in predicting the effective compressive modulus of porous structure

Autor: Yongtao Lu, Yi Huo, Zhuoyue Yang, Yibiao Niu, Ming Zhao, Sergei Bosiakov, Lei Li

Publikováno v: Frontiers in Bioengineering and Biotechnology, Vol 10 (2022)

In recent years, the convolutional neural network (CNN) technique has emerged as an efficient new method for designing porous structure, but a CNN model generally contains a large number of parameters, each of which could influence the predictive abi

Externí odkaz: https://doaj.org/article/8588b108dfff47f99fbf4f2607dbcd3e

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Akademický článek

An Efficient Method for the Inverse Design of Thin-Wall Stiffened Structure Based on the Machine Learning Technique

Autor: Yongtao Lyu, Yibiao Niu, Tao He, Limin Shu, Michael Zhuravkov, Shutao Zhou

Publikováno v: Aerospace, Vol 10, Iss 9, p 761 (2023)

In this paper, a new method using the backpropagation (BP) neural network combined with the improved genetic algorithm (GA) is proposed for the inverse design of thin-walled reinforced structures. The BP neural network model is used to establish the

Externí odkaz: https://doaj.org/article/7473b9bb8da9410d95944e65e9b76f22

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