Real-time energy prediction for a milling machine tool using sparse Gaussian process regression

Abstract

This paper describes a real-time data collection framework and an adaptive machining learning method for constructing a real-time energy prediction model for a machine tool. To effectively establish the energy consumption pattern of a machine tool over time, the energy prediction model is continuously updated with new measurement data to account for time… (More)
DOI: 10.1109/BigData.2015.7363906

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Cite this paper

@article{Park2015RealtimeEP, title={Real-time energy prediction for a milling machine tool using sparse Gaussian process regression}, author={Jinkyoo Park and Kincho H. Law and Raunak Bhinge and Mason Chen and David Dornfeld and Rachuri Sudarsan}, journal={2015 IEEE International Conference on Big Data (Big Data)}, year={2015}, pages={1451-1460} }