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July 12, 2026Aircraft Engineering and Aerospace Technology

A hybrid IDBO-BP-NN model considering work-hardening for surface roughness prediction in two-step milling of GH4169 superalloy

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Authors

GZGuangxu Zhu

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Overview

Randomized trial predicts surface roughness in GH4169 superalloy milling, indicating a new optimization approach.

Key Points

  • The study aims to predict surface roughness in the milling of GH4169 superalloy, considering the work-hardening effect.
  • Proposed a hybrid IDBO-BP-NN model integrating chaotic circle map for initialization.
  • Evaluated predictive performance against BP-NN, GA-BP-NN, PSO-BP-NN, and DBO-BP-NN models.
  • Used mean absolute deviation, mean relative error, mean squared error, and coefficient of determination for performance metrics.
  • IDBO-BP-NN achieved a MAD of 0.051 µm and an R² of 0.969, outperforming all benchmarks.
  • Independent validation showed a maximum relative error of 9.59%, confirming generalization.
  • Finishing cutting speed was identified as the most influential factor, contributing 24.7% to performance.

Cite This Study

Guangxu Zhu (2026) studied this question.

synapsesocial.com/papers/6a532f464f7abc118adecf44https://doi.org/10.1108/aeat-02-2026-0076
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