Tool wear prediction based on XGBoost feature selection combined with PSO-BP network

Tool wear prediction based on XGBoost feature selection combined with PSO-BP network

Abstract To address the challenge of accurately capturing tool wear states in small sample scenarios, this paper proposes a tool wear prediction method that combines XGBoost feature selection with a PSO-BP network. In order to solve the problem of input feature selection and parameter selection in B...

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Bibliographic Details
Main Authors: Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Tool wear prediction
XGBoost
PSO-BP neural network
Online Access:https://doi.org/10.1038/s41598-025-85694-9
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https://doi.org/10.1038/s41598-025-85694-9

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