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Semi-supervised position-dependent milling stability prediction with the loop learning mechanism based on multi-fidelity modeling and artificial neural network

Crossref DOI link: https://doi.org/10.1007/s00170-026-18023-7

Published Online: 2026-04-09

Published Print: 2026-05

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Deng, Congying

Miao, Tianyi

Miao, Jianguo

Lu, Shen
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (51705058)

Science and Technology Research Program of Chongqing Municipal Education Commission (KJZD-K202300611)

Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202300640)

Natural Science Foundation of Chongqing (CSTB2025NSCQ-GPX1292)
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Text and Data Mining valid from 2026-04-09

Version of Record valid from 2026-04-09
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Article History

Received: 20 May 2025

Accepted: 30 March 2026

First Online: 9 April 2026

Declarations

:

: Not applicable.

: The authors declare no competing interests.

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