research-article

Prediction of Mechanical Properties of Hot Rolled Strip Based on DBN and Composite Quantile Regression

Authors:

Tong TianAuthors Info & Claims

ACAI '21: Proceedings of the 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence

Article No.: 110, Pages 1 - 6

https://doi.org/10.1145/3508546.3508656

Published: 25 February 2022 Publication History

Abstract

Tensile strength is a common mechanical property index in strip quality testing. In order to solve the problem of prediction accuracy of mechanical properties of hot rolled strip, a deep belief network and a composite quantile regression model (Deep Belief Network and Composite Quantile Regression, DBN-CQR19) are proposed to predict the tensile strength of hot rolled strip. The model fully considers the robustness of quantile regression, combines the advantage that DBN can learn more abstract hidden layer information from low layer data, and further improves the structure of neural network by using Cuckoo Search (CS) algorithm. The empirical results show that the mean absolute percentage error (MAPE), root mean squared error (RMSE) and mean absolute error (MAE) of the test set of the model are 2.5112, 21.3855 and 13.3780 respectively. The prediction accuracy is higher than that of traditional BP neural network (BPNN), quantile regression neural network (QRNN) and deep belief network (DBN).

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Cited By

Wang JLiu JXia ZChen PLi XChen X(2022)Semi-supervised Labeling Model Based on Gaussian Mixture in the Context of E-commerce Price Fraud2022 4th International Conference on Robotics and Computer Vision (ICRCV)10.1109/ICRCV55858.2022.9953227(300-304)Online publication date: 25-Sep-2022
https://doi.org/10.1109/ICRCV55858.2022.9953227

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ACAI '21: Proceedings of the 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence

December 2021

699 pages

ISBN:9781450385053

DOI:10.1145/3508546

Copyright © 2021 ACM.

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Publication History

Published: 25 February 2022

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ACAI'21

ACAI'21: 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence

December 22 - 24, 2021

Sanya, China

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Cited By

Wang JLiu JXia ZChen PLi XChen X(2022)Semi-supervised Labeling Model Based on Gaussian Mixture in the Context of E-commerce Price Fraud2022 4th International Conference on Robotics and Computer Vision (ICRCV)10.1109/ICRCV55858.2022.9953227(300-304)Online publication date: 25-Sep-2022
https://doi.org/10.1109/ICRCV55858.2022.9953227

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