The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Process data analytics in the era of big data
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Citations
Cites
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
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
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
Greedy layer-wise training of deep networks
Bengio, Y., Lamblin, P., Popovici, D., & Larochelle, H. (2007) · Advances in Neural Information Processing Systems 19 · doi:10.7551/mitpress/7503.003.0024 · Cited by 4,841
The Human Genome Project: Lessons from Large-Scale Biology
Collins, F. S., Morgan, M., & Patrinos, A. (2003) · Science · doi:10.1126/science.1084564 · Cited by 1,284
Cited by
Lei, Y., Jia, F., Lin, J., Xing, S., & Ding, S. X. (2016) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2519325 · Cited by 1,191
Data Mining and Analytics in the Process Industry: The Role of Machine Learning
Ge, Z., Song, Z., Ding, S. X., & Huang, B. (2017) · IEEE Access · doi:10.1109/access.2017.2756872 · Cited by 922
“Qin [286] details the process data analytics in modern industrial processes in the era of big data.”
BackgroundSyafrudin, M., Alfian, G., Fitriyani, N. L., & Rhee, J. (2018) · Sensors · doi:10.3390/s18092946 · Cited by 401
In silico ADME/T modelling for rational drug design
Wang, Y., Xing, J., Xu, Y., Zhou, N., Peng, J., Xiong, Z., Liu, X., Luo, X., Luo, C., Chen, K., et al. (2015) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583515000190 · Cited by 367
Advances and opportunities in machine learning for process data analytics
Qin, S. J., & Chiang, L. H. (2019) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2019.04.003 · Cited by 351
Self-citation
Metadata
- Authors
- Qin, S. J.
- Venue
- AIChE Journal
- Publisher
- Wiley
- Published
- 2014-07-02
- Volume
- 60
- Issue
- 9
- Pages
- 3092-3100
- ISSN
- 0001-1541 (ISSN-L)
- 1547-5905
- OpenAlex
- W2106849258
- Cited by
- 383
- References
- 5
- FWCI
- 47.58
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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- CoChat. (2026). Citation check: Process data analytics in the era of big data. https://app.cochat.ai/papers/10.1002/aic.14523
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- Qin, S. J. (2014). Process data analytics in the era of big data. AIChE Journal. https://doi.org/10.1002/aic.14523
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.
