Andrew Longstaff
Orcid: 0000-0002-2886-3305
According to our database1,
Andrew Longstaff
authored at least 18 papers
between 2011 and 2022.
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Bibliography
2022
Int. J. Autom. Technol., 2022
2020
Int. J. Autom. Technol., 2020
2017
Sensors, 2017
A cuckoo search optimisation-based Grey prediction model for thermal error compensation on CNC machine tools.
Grey Syst. Theory Appl., 2017
Expedient identification of the dynamics of ball-screw drives using online-validation.
Proceedings of the 23rd International Conference on Automation and Computing, 2017
On the Exploitation of Automated Planning for Reducing Machine Tools Energy Consumption between Manufacturing Operations.
Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling, 2017
2016
A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information.
Proceedings of the 22nd International Conference on Automation and Computing, 2016
2015
Expert Syst. Appl., 2015
The application of ANFIS prediction models for thermal error compensation on CNC machine tools.
Appl. Soft Comput., 2015
2014
Eng. Appl. Artif. Intell., 2014
A novel approach for ANFIS modelling based on Grey system theory for thermal error compensation.
Proceedings of the 14th UK Workshop on Computational Intelligence, 2014
Automated Planning for Multi-Objective Machine Tool Calibration: Optimising Makespan and Measurement Uncertainty.
Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling, 2014
2013
Model-based expert system to automatically adapt milling forces in Pareto optimal multi-objective working points.
Expert Syst. Appl., 2013
Control Scheme for Automatically Controlling the Milling System in between Optimal Working Points.
Proceedings of the IEEE International Conference on Systems, 2013
2012
Expert Syst. Appl., 2012
Proceedings of the Twenty-Second International Conference on Automated Planning and Scheduling, 2012
2011
Proceedings of the 17th International Conference on Automation and Computing, 2011
A fast and effective way to improve the merging accuracy of multi-view point cloud data.
Proceedings of the 17th International Conference on Automation and Computing, 2011