The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index.
Practical options for selecting data-driven or physics-based prognostics algorithms with reviews
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Citations
Cites
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Learning Internal Representations by Error Propagation
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1985) · doi:10.21236/ada164453 · Cited by 16,172
Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
On Estimation of a Probability Density Function and Mode
Parzen, E. (1962) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177704472 · Cited by 10,585
Sequential Monte Carlo Methods in Practice
(2001) · Springer eBooks · doi:10.1007/978-1-4757-3437-9 · Cited by 7,366
A Critical Analysis of Crack Propagation Laws
Paris, P., & Erdogan, F. (1963) · Journal of Basic Engineering · doi:10.1115/1.3656900 · Cited by 7,122
Design and Analysis of Computer Experiments
Sacks, J., Welch, W. J., Mitchell, T. J., & Wynn, H. P. (1989) · Statistical Science · doi:10.1214/ss/1177012413 · Cited by 6,919
A review on machinery diagnostics and prognostics implementing condition-based maintenance
Jardine, A. K. S., Lin, D., & Banjevic, D. (2006) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2005.09.012 · Cited by 4,816
Cited by
A review on prognostics and health management (PHM) methods of lithium-ion batteries
Meng, H., & Li, Y.-F. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.109405 · Cited by 389
Remaining useful life prediction of aircraft engine based on degradation pattern learning
Zhao, Z., Liang, B., Wang, X., & Lu, W. (2017) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2017.02.007 · Cited by 267
Javed, K., Gouriveau, R., & Zerhouni, N. (2017) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2017.01.050 · Cited by 217
An Improved Generic Hybrid Prognostic Method for RUL Prediction Based on PF-LSTM Learning
Xue, K., Yang, J., Yang, M., & Wang, D. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3251391 · Cited by 75
Qin, T., Zeng, S., Guo, J., & Skaf, Z. (2016) · Energies · doi:10.3390/en9110896 · Cited by 52
Metadata
- Authors
- An, D., Kim, N. H., & Choi, J.-H.
- Venue
- Reliability Engineering & System Safety
- Publisher
- Elsevier BV
- Published
- 2015-01
- Volume
- 133
- Pages
- 223-236
- ISSN
- 0951-8320 (ISSN-L)
- OpenAlex
- W2051319254
- Cited by
- 451
- References
- 99
- FWCI
- 43.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Practical options for selecting data-driven or physics-based prognostics algorithms with reviews. https://app.cochat.ai/papers/10.1016/j.ress.2014.09.014
- The paper
- An, D., Kim, N. H., & Choi, J.-H. (2015). Practical options for selecting data-driven or physics-based prognostics algorithms with reviews. Reliability Engineering & System Safety. https://doi.org/10.1016/j.ress.2014.09.014
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
