The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
An insight into machine-learning algorithms to model human-caused wildfire occurrence
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Citations
Cites
R: A Language and Environment for Statistical Computing
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The Nature of Statistical Learning Theory
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The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
Classification and Regression by randomForest
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
John Lu, Z. Q. (2010) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.2010.00646_6.x · Cited by 12,390
Novel methods improve prediction of species’ distributions from occurrence data
Elith*, J., H. Graham*, C., P. Anderson, R., Dudík, M., Ferrier, S., Guisan, A., J. Hijmans, R., Huettmann, F., R. Leathwick, J., Lehmann, A., et al. (2006) · Ecography · doi:10.1111/j.2006.0906-7590.04596.x · Cited by 9,088
Cited by
Jaafari, A., Zenner, E. K., Panahi, M., & Shahabi, H. (2019) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2018.12.015 · Cited by 299
Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction
Pham, B. T., Jaafari, A., Avand, M., Al-Ansari, N., Dinh Du, T., Yen, H. P. H., Phong, T. V., Nguyen, D. H., Le, H. V., Mafi-Gholami, D., et al. (2020) · Symmetry · doi:10.3390/sym12061022 · Cited by 284
A review of Earth Artificial Intelligence
Sun, Z., Sandoval, L., Crystal-Ornelas, R., Mousavi, S. M., Wang, J., Lin, C., Cristea, N., Tong, D., Carande, W. H., Ma, X., et al. (2022) · Computers & Geosciences · doi:10.1016/j.cageo.2022.105034 · Cited by 271
Deploying artificial intelligence for climate change adaptation
Leal Filho, W., Wall, T., Rui Mucova, S. A., Nagy, G. J., Balogun, A.-L., Luetz, J. M., Ng, A. W., Kovaleva, M., Safiul Azam, F. M., Alves, F., et al. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121662 · Cited by 266
Metadata
- Authors
- Rodrigues, M., & de la Riva, J.
- Venue
- Environmental Modelling & Software
- Publisher
- Elsevier BV
- Published
- 2014-07
- Volume
- 57
- Pages
- 192-201
- ISSN
- 1364-8152 (ISSN-L)
- OpenAlex
- W1964647807
- Cited by
- 292
- References
- 62
- FWCI
- 5.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: An insight into machine-learning algorithms to model human-caused wildfire occurrence. https://app.cochat.ai/papers/10.1016/j.envsoft.2014.03.003
- The paper
- Rodrigues, M., & de la Riva, J. (2014). An insight into machine-learning algorithms to model human-caused wildfire occurrence. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2014.03.003
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.
