Thermal error measurement and modelling in machine tools. Part II. Hybrid Bayesian Network—support vector machine model-Reference-Cited by-同舟云学术

Thermal error measurement and modelling in machine tools. Part II. Hybrid Bayesian Network—support vector machine model

Published:2003-03 Issue:4 Volume:43 Page:405-419
ISSN:0890-6955
Container-title:International Journal of Machine Tools and Manufacture
language:en
Short-container-title:International Journal of Machine Tools and Manufacture

Author:

Ramesh R.,Mannan M.A.,Poo A.N.,Keerthi S.S.

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Reference26 articles.

1. A study of thermally induced machine tool errors in real cutting conditions;Chen;International Journal of Machine Tools and Manufacture,1996

2. Fast calibration and modelling of thermally induced machine tool errors in real machining;Chen;International Journal of Machine Tools and Manufacture,1997

3. An introduction to support vector machines: and other kernel-based learning methods;Cristianini,2000

4. S. Gunn, Support vector machines for classification and regression, ISIS Technical Report, Image Speech and Intelligent Systems Group, University of Southampton, 1998.

5. Neural Networks—A Comprehensive Foundation;Haykin,1999

Cited by 93 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Thermal error prediction of ball screws in full-time series using working condition data based on a mechanism and data hybrid-driven model;The International Journal of Advanced Manufacturing Technology;2024-06-01

2. Geometric Error Measurement of Rotary Axes on Five-Axis Machine Tools: A Review;International Journal of Precision Engineering and Manufacturing;2024-04-13

3. Spindle unit thermal error modeling and compensation based on digital twin;The International Journal of Advanced Manufacturing Technology;2024-03-21

4. CNN and ANN Based Tool Condition Monitoring in Gear Machining Using Audio and Vibration Signals Via Cost Effective Sensors;2024 International Conference on Emerging Smart Computing and Informatics (ESCI);2024-03-05

5. Enhancing four-axis machining center accuracy through interactive fusion of spatiotemporal graph convolutional networks and an error-controlled digital twin system;Journal of Manufacturing Processes;2024-02