CNN model.

<div><p>The study aims to explore quality prediction in ceramic bearing grinding processing, with particular focus on the effect of grinding parameters on surface roughness. The study uses active learning regression model for model construction and optimization, and empirical analysis of...

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Bibliographic Details
Main Author:	Longfei Gao (698900) (author)
Other Authors:	Yuhou Wu (21011498) (author), Jian Sun (27858) (author), Junxing Tian (21011501) (author)
Published:	2025
Subjects:	Ecology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified ra value drops average training loss 21 &# 956 1876 &# 956 1624 &# 956 015 &# 8201 provide theoretical support experimental setup covers experiment also found grinding depth increases explore quality prediction different grinding conditions different conditions also provide grinding depth quality prediction grinding processing grinding parameters grinding mechanism surface quality machining quality xlink "> surface roughness significantly improve particular focus moderately adjusting feed rate experimental results empirical analysis conduct experiments ceramic bearings actual production
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CNN model.

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