The DOI matches its Crossref record; 209 of the 209 references it cites were found in a registry or an index.
Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data
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Cites
Data mining: concepts and techniques
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Data Mining: Practical Machine Learning Tools and Techniques
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Statistical Analysis With Missing Data
Lahiff, M., Little, R. J. A., & Rubin, D. B. (1989) · Journal of the American Statistical Association · doi:10.2307/2289883 · Cited by 17,265
Extreme learning machine: Theory and applications
Huang, G.-B., Zhu, Q.-Y., & Siew, C.-K. (2006) · Neurocomputing · doi:10.1016/j.neucom.2005.12.126 · Cited by 13,285
Advances in Neural Information Processing Systems 25
Zhang, Y., Sutton, C. A., Storkey, A., & Zoubin Ghahramani, A. (2012) · Cited by 12,653
Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
Independent component analysis, A new concept?
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Cited by
Greenacre, M., Groenen, P. J. F., Hastie, T., D’Enza, A. I., Markos, A., & Tuzhilina, E. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00184-w · Cited by 1,773
A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes
Jiang, Y., Yin, S., Dong, J., & Kaynak, O. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3033153 · Cited by 667
An incorrect data detection method for big data cleaning of machinery condition monitoring
Xu, X., Lei, Y., & Li, Z. (2020) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2019.2903774 · Cited by 134
Variable time delay estimation in continuous industrial processes
Cattaldo, M., Ferrer, A., & Måge, I. (2024) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2024.105082 · Cited by 18
Demilitarized network to secure the data stored in industrial networks
Nuñez Alvarez, J. R., Zamora, Y. P., Pina, I. B., & Angarita, E. N. (2021) · International Journal of Electrical and Computer Engineering (IJECE) · doi:10.11591/ijece.v11i1.pp611-619 · Cited by 10
Metadata
- Authors
- Zhu, J., Ge, Z., Song, Z., & Gao, F.
- Venue
- Annual Reviews in Control
- Publisher
- Elsevier BV
- Published
- 2018
- Volume
- 46
- Pages
- 107-133
- ISSN
- 1367-5788 (ISSN-L)
- OpenAlex
- W2895250764
- Cited by
- 308
- References
- 209
- FWCI
- 18.15
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhu, J., Ge, Z., Song, Z., & Gao, F. (2018). Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data. Annual Reviews in Control. https://doi.org/10.1016/j.arcontrol.2018.09.003
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.