The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone
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Citations
Cites
Approximation by superpositions of a sigmoidal function
Cybenko, G. (1989) · Mathematics of Control, Signals, and Systems · doi:10.1007/bf02551274 · Cited by 13,883
Bates, J. M., & Granger, C. W. J. (1969) · Journal of the Operational Research Society · doi:10.1057/jors.1969.103 · Cited by 3,201
Effects of ambient particulate matter and ozone on daily mortality in Rotterdam, the Netherlands
Hoek, G., Schwartz, J. D., Groot, B., & Eilers, P. (1997) · Archives of Environmental Health An International Journal · doi:10.1080/00039899709602224 · Cited by 133
Cited by
A review of artificial neural network models for ambient air pollution prediction
Cabaneros, S. M., Calautit, J. K., & Hughes, B. R. (2019) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2019.06.014 · Cited by 459
Forecasting air quality time series using deep learning
Freeman, B. S., Taylor, G., Gharabaghi, B., & Thé, J. (2018) · Journal of the Air & Waste Management Association · doi:10.1080/10962247.2018.1459956 · Cited by 319
Non-linear variable selection for artificial neural networks using partial mutual information
May, R. J., Maier, H. R., Dandy, G. C., & Fernando, T. M. K. G. (2008) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2008.03.007 · Cited by 310
Metadata
- Authors
- ALALAWI, S., ABDULWAHAB, S., & BAKHEIT, C.
- Venue
- Environmental Modelling & Software
- Publisher
- Elsevier BV
- Published
- 2008-04
- Volume
- 23
- Issue
- 4
- Pages
- 396-403
- ISSN
- 1364-8152 (ISSN-L)
- OpenAlex
- W2022668092
- Cited by
- 200
- References
- 3
- FWCI
- 8.97
- 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.
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- CoChat. (2026). Citation check: Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone. https://app.cochat.ai/papers/10.1016/j.envsoft.2006.08.007
- The paper
- ALALAWI, S., ABDULWAHAB, S., & BAKHEIT, C. (2008). Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2006.08.007
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.
