The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
A hybrid framework combining data-driven and model-based methods for system remaining useful life prediction
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Remaining useful life estimation – A review on the statistical data driven approaches
Si, X.-S., Wang, W., Hu, C.-H., & Zhou, D.-H. (2011) · European Journal of Operational Research · doi:10.1016/j.ejor.2010.11.018 · Cited by 2,162
Prognostic modelling options for remaining useful life estimation by industry
Sikorska, J. Z., Hodkiewicz, M., & Ma, L. (2011) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2010.11.018 · Cited by 947
Comparison of resampling schemes for particle filtering
Douc, R., & Cappe, O. (2005) · ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005. · doi:10.1109/ispa.2005.195385 · Cited by 806
Prognostics in Battery Health Management
Goebel, K., Saha, B., Saxena, A., Celaya, J., & Christophersen, J. (2008) · IEEE Instrumentation & Measurement Magazine · doi:10.1109/mim.2008.4579269 · Cited by 594
Metrics for evaluating performance of prognostic techniques
Saxena, A., Celaya, J., Balaban, E., Goebel, K., Saha, B., Saha, S., & Schwabacher, M. (2008) · 2008 International Conference on Prognostics and Health Management · doi:10.1109/phm.2008.4711436 · Cited by 518
A similarity-based prognostics approach for Remaining Useful Life estimation of engineered systems
Wang, T., Yu, J., Siegel, D., & Lee, J. (2008) · 2008 International Conference on Prognostics and Health Management · doi:10.1109/phm.2008.4711421 · Cited by 474
Remaining Useful Life Estimation of Critical Components With Application to Bearings
Medjaher, K., Tobon-Mejia, D. A., & Zerhouni, N. (2012) · IEEE Transactions on Reliability · doi:10.1109/tr.2012.2194175 · Cited by 292
A data-model-fusion prognostic framework for dynamic system state forecasting
Liu, J., Wang, W., Ma, F., Yang, Y. B., & Yang, C. S. (2012) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2012.02.015 · Cited by 190
Guo, H., Watson, S. J., Tavner, P., & Xiang, J. (2009) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2008.12.004 · Cited by 178
2006 IEEE Aerospace Conference
(2006) · doi:10.1109/ieeeconf11031.2006 · Cited by 150
Cited by
Zhou, Y., & Huang, M. (2016) · Microelectronics Reliability · doi:10.1016/j.microrel.2016.07.151 · Cited by 285
Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis
Nascimento, R. G., Corbetta, M., Kulkarni, C. S., & Viana, F. A. C. (2021) · Journal of Power Sources · doi:10.1016/j.jpowsour.2021.230526 · Cited by 224
Hannan, M. A., How, D. N. T., Lipu, M. S. H., Mansor, M., Ker, P. J., Dong, Z. Y., Sahari, K. S. M., Tiong, S. K., Muttaqi, K. M., Mahlia, T. M. I., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-98915-8 · Cited by 196
Metadata
- Authors
- Liao, L., & Köttig, F.
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 44
- Pages
- 191-199
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W2337713278
- Cited by
- 258
- References
- 18
- FWCI
- 28.70
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A hybrid framework combining data-driven and model-based methods for system remaining useful life prediction. https://app.cochat.ai/papers/10.1016/j.asoc.2016.03.013
- The paper
- Liao, L., & Köttig, F. (2016). A hybrid framework combining data-driven and model-based methods for system remaining useful life prediction. Applied Soft Computing. https://doi.org/10.1016/j.asoc.2016.03.013
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.
