Prediction of mechanical properties of hot-rolled steel based on multi-channel convolutional neural network-Reference-Cited by-同舟云学术

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Prediction of mechanical properties of hot-rolled steel based on multi-channel convolutional neural network

Published:2023-11-24 Issue: Volume: Page:252-257
ISSN:
Container-title:Proceedings of the 2023 5th International Conference on Internet of Things, Automation and Artificial Intelligence
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Author:

Wang Zhengzhong¹^ORCID,Wang Shengdong¹^ORCID,Zhang Kai¹^ORCID,Tang Xingchang²^ORCID,Wang Yichao³^ORCID

Affiliation:

1. Jiugang Group Carbon Steel Sheet Factory, China

2. State Key Laboratory of Advanced Processing and Recycling of Nonferrous Metals, Lanzhou University of Technology, China

3. College of Computer and Communication, Lanzhou University of Technology, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3653081.3653123

Reference11 articles.

1. Prediction of bending force in the hot strip rolling process using artificial neural network and genetic algorithm (ANN-GA)

2. Wu, Y., & Ren, Y. 2011, September. Prediction of mechanical properties of hot rolled strips by BP artificial neural network. In 2011 International Conference of Information Technology, Computer Engineering and Management Sciences (Vol. 1, pp. 15-17). IEEE.

3. Chou, P. Y., Tsai, J. T., & Chou, J. H. 2016. Modeling and optimizing tensile strength and yield point on a steel bar using an artificial neural network with taguchi particle swarm optimizer. IEEE access, 4, 585-593.

4. Online mechanical property prediction system for hot rolled IF steel

5. Experimental parameter sensitivity analysis of residual stresses induced by deep rolling on 7075-T6 aluminium alloy

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