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Self learning research on rolling force model of hot strip rolling based on improved adaptive difference

X. L. Xi orcid.org/0000-0002-7410-5783 ; Institute of Applied Technology, University of Science and Technology Liaoning, China
B. Wang ; Institute of Applied Technology, University of Science and Technology Liaoning, China

Sažetak

In order to improve the prediction accuracy of the rolling force Self-learning Model and change the phenomenon that the learning coefficient is unstable and the optimization process is not reasonable due to the experience value of the self-learning factor in the traditional self-learning, this paper proposes an improved adaptive differential evolution (IADE) algorithm based on the standard differential evolution algorithm to solve and optimize the problem quickly. The prediction accuracy of rolling force model is improved. The experimental results show that the prediction accuracy of IADE algorithm is lower than that of the traditional model, which can effectively improve the prediction accuracy.

Ključne riječi

strip; hot-rolling; rolling force; deformation resistance; stress state

Hrčak ID:

262412

URI

https://hrcak.srce.hr/262412

Datum izdavanja:

3.1.2022.

Posjeta: 1.437 *