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<p>In order to eliminate the predicted bias of the traditional Sims model, a new method, called the composite rectification method, is proposed. First, the deformation resistance model was built based on the generalized additive principle. This new model was adopted to replace the deformation resistance model in the Sims model. Through this factor replacement, the deformation resistance bias due to the traditional regression method was eliminated. Secondly, to solve the mathematical form imperfection caused by the introduction of assumptions during the derivation of the Sims model, a back propagation (BP) neural network model on the bias of the once-time corrected Sims model was built. Ultimately, the double correction of the Sims model was realized through the additive compensation method, and an integrated model of rolling force was ultimately obtained. The composite rectification method presented in this article can provide a new way of modeling complex systems with high precision.</p>

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Rolling force modeling based on neural network and mechanism model

  • 期刊论文

  • 发表日期：

    2025年1月31日

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  • Xiao Xiao Guo,
  • Shun Hu Zhang,
  • Li Wang,
  • Wei Gang Li,
  • Lei Zhang

摘要

In order to eliminate the predicted bias of the traditional Sims model, a new method, called the composite rectification method, is proposed. First, the deformation resistance model was built based on the generalized additive principle. This new model was adopted to replace the deformation resistance model in the Sims model. Through this factor replacement, the deformation resistance bias due to the traditional regression method was eliminated. Secondly, to solve the mathematical form imperfection caused by the introduction of assumptions during the derivation of the Sims model, a back propagation (BP) neural network model on the bias of the once-time corrected Sims model was built. Ultimately, the double correction of the Sims model was realized through the additive compensation method, and an integrated model of rolling force was ultimately obtained. The composite rectification method presented in this article can provide a new way of modeling complex systems with high precision.