Abstract
Considering the prediction of thermal machine tool error data this paper proposes using GM (1,1) model of gray system to predict machine tool thermal error data. Through comparing with the calculated result between traditional GM(1,1) model and the optimized GM(1,1) model, more satisfactory results can be achieved, and indicating that this model can predict the distribution of machine tool thermal error data more accurately. So the optimized GM (1,1) model can be used to provide a more reliable methodology in controlling the digital machine tool.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
