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2020 – today
- 2023
[c3]Ricardo Ludeke, P. Stephan Heyns:
Towards a Deep Reinforcement Learning based approach for real time decision making and resource allocation for Prognostics and Health Management applications. ICPHM 2023: 20-29- [i4]Ryan Balshaw, P. Stephan Heyns, Daniel N. Wilke, Stephan Schmidt:
A spectral regularisation framework for latent variable models designed for single channel applications. CoRR abs/2310.19246 (2023) - 2021
- [j12]Bradley Dean Collins
, P. Stephan Heyns, Schalk Kok, Daniel N. Wilke:
Application of Anti-Diagonal Averaging in Response Reconstruction. Symmetry 13(7): 1165 (2021) - 2020
- [j11]Stephan Schmidt, Radoslaw Zimroz, Fakher Chaari, P. Stephan Heyns, Mohamed Haddar:
A Simple Condition Monitoring Method for Gearboxes Operating in Impulsive Environments. Sensors 20(7): 2115 (2020)
2010 – 2019
- 2018
- [j10]Sylvester A. Aye, P. Stephan Heyns:
Prognostics of slow speed bearings using a composite integrated Gaussian process regression model. Int. J. Prod. Res. 56(14): 4860-4873 (2018) - 2017
- [j9]Antoine S. D. Dymond, Schalk Kok, P. Stephan Heyns:
MOTA: A Many-Objective Tuning Algorithm Specialized for Tuning under Multiple Objective Function Evaluation Budgets. Evol. Comput. 25(1): 113-141 (2017) - 2015
- [j8]Sylvester A. Aye, P. Stephan Heyns:
Acoustic Emission-Based Prognostics of Slow Rotating Bearing Using Bayesian Techniques Under Dependent and Independent Samples. Appl. Artif. Intell. 29(6): 563-596 (2015) - [j7]Antoine S. D. Dymond, Andries P. Engelbrecht, Schalk Kok, P. Stephan Heyns:
Tuning Optimization Algorithms Under Multiple Objective Function Evaluation Budgets. IEEE Trans. Evol. Comput. 19(3): 341-358 (2015) - 2014
- [j6]Burkhard H. Freyer, P. Stephan Heyns, Nico J. Theron:
Comparing orthogonal force and unidirectional strain component processing for tool condition monitoring. J. Intell. Manuf. 25(3): 473-487 (2014) - 2013
- [c2]Antoine S. D. Dymond, Schalk Kok, P. Stephan Heyns:
The sensitivity of multi-objective optimization algorithm performance to objective function evaluation budgets. IEEE Congress on Evolutionary Computation 2013: 1868-1875 - 2012
- [j5]T. Heyns, Johan Pieter de Villiers, P. Stephan Heyns:
Consistent haul road condition monitoring by means of vehicle response normalisation with Gaussian processes. Eng. Appl. Artif. Intell. 25(8): 1752-1760 (2012) - 2011
- [j4]Kesheng Wang, P. Stephan Heyns:
An empirical re-sampling method on intrinsic mode function to deal with speed variation in machine fault diagnostics. Appl. Soft Comput. 11(8): 5015-5027 (2011) - [j3]Sukhomay Pal, P. Stephan Heyns, Burkhard H. Freyer, Nico J. Theron, Surjya K. Pal:
Tool wear monitoring and selection of optimum cutting conditions with progressive tool wear effect and input uncertainties. J. Intell. Manuf. 22(4): 491-504 (2011) - [c1]Antoine S. D. Dymond, Andries P. Engelbrecht, P. Stephan Heyns:
The sensitivity of single objective optimization algorithm control parameter values under different computational constraints. IEEE Congress on Evolutionary Computation 2011: 1412-1419
2000 – 2009
- 2009
- [j2]M. A. Herzog, Tshilidzi Marwala, P. Stephan Heyns:
Machine and component residual life estimation through the application of neural networks. Reliab. Eng. Syst. Saf. 94(2): 479-489 (2009) - 2007
- [i3]M. A. Herzog, Tshilidzi Marwala, P. Stephan Heyns:
Machine and Component Residual Life Estimation through the Application of Neural Networks. CoRR abs/0705.1390 (2007) - [i2]L. Mdlazi, Tshilidzi Marwala, CJ Stander, Cornie Scheffer, P. Stephan Heyns:
Principal Component Analysis and Automatic Relevance Determination in Damage Identification. CoRR abs/0705.1672 (2007) - [i1]L. Mdlazi, CJ Stander, P. Stephan Heyns, Tshilidzi Marwala:
Using artificial intelligence for data reduction in mechanical engineering. CoRR abs/0705.1673 (2007) - 2005
- [j1]Cornie Scheffer, Herman A. Engelbrecht, P. Stephan Heyns:
A comparative evaluation of neural networks and hidden Markov models for monitoring turning tool wear. Neural Comput. Appl. 14(4): 325-336 (2005)
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