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2020 – today
- 2023
[i1]Hao Lu, Austin M. Bray, Chao Hu, Andrew T. Zimmerman, Hongyi Xu:
An interpretable deep learning method for bearing fault diagnosis. CoRR abs/2308.10292 (2023)- 2022
- [j3]Hao Lu
, Vahid Barzegar, Venkat Nemani, Chao Hu, Simon Laflamme, Andrew T. Zimmerman:
Joint training of a predictor network and a generative adversarial network for time series forecasting: A case study of bearing prognostics. Expert Syst. Appl. 203: 117415 (2022) - [j2]Venkat Nemani, Hao Lu, Adam Thelen, Chao Hu, Andrew T. Zimmerman:
Ensembles of probabilistic LSTM predictors and correctors for bearing prognostics using industrial standards. Neurocomputing 491: 575-596 (2022) - 2021
- [c3]Hao Lu, Vahid Barzegar, Venkat Nemani, Chao Hu, Simon Laflamme, Andrew T. Zimmerman:
GAN-LSTM Predictor for Failure Prognostics of Rolling Element Bearings. ICPHM 2021: 1-8
2010 – 2019
- 2013
- [j1]Andrew T. Zimmerman, Jerome P. Lynch, Frank T. Ferrese:
Market-based resource allocation for distributed data processing in wireless sensor networks. ACM Trans. Embed. Comput. Syst. 12(3): 84:1-84:28 (2013)
2000 – 2009
- 2009
- [c2]Andrew T. Zimmerman, Jerome P. Lynch, Frank T. Ferrese:
Market-based computational task assignment within autonomous wireless sensor networks. EIT 2009: 23-28 - 2007
- [c1]Andrew T. Zimmerman, Jerome P. Lynch:
Parallelized Simulated Annealing for Model Updating in Ad-Hoc Wireless Sensing Networks. MDM 2007: 341-345
Coauthor Index
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