Takip et
Divish Rengasamy
Divish Rengasamy
Institute for Aerospace Technology, University of Nottingham
nottingham.ac.uk üzerinde doğrulanmış e-posta adresine sahip
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Deep learning with dynamically weighted loss function for sensor-based prognostics and health management
D Rengasamy, M Jafari, B Rothwell, X Chen, GP Figueredo
Sensors 20 (3), 723, 2020
1112020
Deep learning approaches to aircraft maintenance, repair and overhaul: A review
D Rengasamy, HP Morvan, GP Figueredo
2018 21st International Conference on Intelligent Transportation Systems …, 2018
512018
Feature importance in machine learning models: A fuzzy information fusion approach
D Rengasamy, JM Mase, A Kumar, B Rothwell, MT Torres, MR Alexander, ...
Neurocomputing 511, 163-174, 2022
472022
Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion
D Rengasamy, BC Rothwell, GP Figueredo
Applied Sciences 11 (24), 11854, 2021
392021
Machine learning to determine the main factors affecting creep rates in laser powder bed fusion
S Sanchez, D Rengasamy, CJ Hyde, GP Figueredo, B Rothwell
Journal of Intelligent Manufacturing 32 (8), 2353-2373, 2021
302021
Load prediction using support vector regression
LW Chong, D Rengasamy, YW Wong, RK Rajkumar
TENCON 2017-2017 IEEE Region 10 Conference, 1069-1074, 2017
192017
Asymmetric loss functions for deep learning early predictions of remaining useful life in aerospace gas turbine engines
D Rengasamy, B Rothwell, GP Figueredo
2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020
172020
Anomaly detection for unmanned aerial vehicle sensor data using a stacked recurrent autoencoder method with dynamic thresholding
V Bell, D Rengasamy, B Rothwell, GP Figueredo
arXiv preprint arXiv:2203.04734, 2022
162022
System condition monitoring through Bayesian change point detection using pump vibrations
E Tochev, D Rengasamy, H Pfifer, S Ratchev
2020 IEEE 16th International Conference on Automation Science and …, 2020
42020
An intelligent toolkit for benchmarking data-driven aerospace prognostics
D Rengasamy, JM Mase, B Rothwell, GP Figueredo
2019 IEEE intelligent transportation systems conference (ITSC), 4210-4215, 2019
42019
Mechanistic interpretation of machine learning inference: A fuzzy feature importance fusion approach
D Rengasamy, JM Mase, MT Torres, B Rothwell, DA Winkler, ...
arXiv preprint arXiv:2110.11713, 2021
32021
Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion
D Rengasamy, B Rothwell, G Figueredo
arXiv preprint arXiv:2009.05501, 2020
32020
EFI: A Toolbox for Feature Importance Fusion and Interpretation in Python
A Kumar, JM Mase, D Rengasamy, B Rothwell, MT Torres, DA Winkler, ...
International Conference on Machine Learning, Optimization, and Data Science …, 2022
22022
Deep Learning Approaches to Aircraft Maintenance
D Rengasamy, HP Morvan, GP Figueredo
Repair and Overhaul: A Review, 150-156, 2018
22018
Embedding and Extracting Domain Knowledge in Machine Learning for Condition-based Maintenance
D Rengasamy
University of Nottingham, 0
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