Open Access
Issue |
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|
|
---|---|---|
Article Number | 01006 | |
Number of page(s) | 5 | |
Section | Network Security System, Neural Network and Data Information | |
DOI | https://doi.org/10.1051/matecconf/201823201006 | |
Published online | 19 November 2018 |
- Wang Q, L, Huang W D, Chen Z. Online monitoring and analysis system for energy efficiency of NC machine tools [J]. Modern Manufacturing Engineering, 2015, 3(1): 39-47. [Google Scholar]
- Dai X D, Wang X, Bi X G, Interpretation of world energy supply and demand in 2015[J]. Natural gas and petroleum, 2017, 35(1): 1-4. [Google Scholar]
- Kashiwa H, Sato R, Hayashi A, et al. S131011 Energy Consumption of Spindle and Feed Drive Systems of NC Machine Tool in End-milling Operation[J]. Journal of Cleaner Production, 2013, 2013:_S131011-1-_S131011-5. [Google Scholar]
- Zhao G, Wang Q, Ruan D. Analysis of power efficiency for dry milling machine based on response surface of machining parameters [J]. China Mechanical Engineering, 2016, 27(21): 2944-2948. [Google Scholar]
- Jayasinghe J, Nadishan K. Neural network based state of charge (SOC) estimation of electric vehicle batteries [J] University of Moratuwa, 2014, 4 (12): 1-4. [Google Scholar]
- Cai Wei, Liu Fei, et al An energy management approach for the mechanical manufacture industry through developing a multi-object energy benchmark [J]. Energy Conversion and Management, 2017,132:361-371. [CrossRef] [Google Scholar]
- Kant G, Sangwan K S. Predictive Modelling for Energy Consumption in Machining Using Artificial Neural Network [J] ProcardiaCrip, 2015, 37: 205-210. [Google Scholar]
- VINCENT Aizebeoje Blowguns, PAUL Tarisai Mativenga. Modelling of Direct Energy Requirement in Mechanical Machining Processes [J]. Journal of Cleaner Production, 2013,41:179-186. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.