Back Propagation Neural Network-Based Predictive Model for Magnetorheological–Chemical Polishing of Silicon Carbide

Back Propagation Neural Network-Based Predictive Model for Magnetorheological–Chemical Polishing of Silicon Carbide

Magnetorheological–chemical-polishing tests are carried out on single-crystal silicon carbide (SiC) to study the influence of the process parameters on the polishing effect, predict the polishing results via a back propagation (BP) neural network, and construct a model of the processing parameters t...

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Bibliographic Details
Main Authors: Huazhuo Liang, Wenjie Chen, Youzhi Fu, Wenjie Zhou, Ling Mo, Yue Jian, Qi Wen, Dawei Liu, Junfeng He
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Micromachines
Subjects:
magnetorheological–chemical polishing
SiC
BP neural network
modelling and prediction
Online Access:https://www.mdpi.com/2072-666X/16/3/271
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