A novel integrated TDLAVOA-XGBoost model for tool wear prediction in lathe and milling operations
Tool wear in machining operations compromises tool lifespan and performance. Machine learning models, particularly eXtreme Gradient Boosting (XGBoost), demonstrate pattern recognition capabilities for such predictions. However, their effectiveness is highly dependent on hyperparameters, and empirica...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025020560 |
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