The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.
A hybrid artificial intelligence approach using GIS-based neural-fuzzy inference system and particle swarm optimization for forest fire susceptibility modeling at a tropical area
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Citations
Cites
Particle swarm optimization: An overview
Poli, R., Kennedy, J., & Blackwell, T. (2007) · Swarm Intelligence · doi:10.1007/s11721-007-0002-0 · Cited by 21,101
ANFIS: adaptive-network-based fuzzy inference system
Jang, J.-S. R. (1993) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/21.256541 · Cited by 16,254
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
(2019) · Handbook of Machine Learning · doi:10.1142/9789811205675_0004 · Cited by 6,270
An assessment of the effectiveness of a random forest classifier for land-cover classification
Rodriguez-Galiano, V. F., Ghimire, B., Rogan, J., Chica-Olmo, M., & Rigol-Sanchez, J. P. (2012) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2011.11.002 · Cited by 2,907
Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information
Benz, U. C., Hofmann, P., Willhauck, G., Lingenfelder, I., & Heynen, M. (2004) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2003.10.002 · Cited by 2,530
Terrestrial ecosystem carbon dynamics and climate feedbacks
Heimann, M., & Reichstein, M. (2008) · Nature · doi:10.1038/nature06591 · Cited by 1,578
Rethinking receiver operating characteristic analysis applications in ecological niche modeling
Peterson, A. T., Papeş, M., & Soberón, J. (2008) · Ecological Modelling · doi:10.1016/j.ecolmodel.2007.11.008 · Cited by 1,526
Geographic information systems for geoscientists: modelling with GIS
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COMPARING THE PALMER DROUGHT INDEX AND THE STANDARDIZED PRECIPITATION INDEX1
Guttman, N. B. (1998) · JAWRA Journal of the American Water Resources Association · doi:10.1111/j.1752-1688.1998.tb05964.x · Cited by 1,140
Cited by
Zhang, G., Wang, M., & Liu, K. (2019) · International Journal of Disaster Risk Science · doi:10.1007/s13753-019-00233-1 · Cited by 341
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
Current status and applications of Artificial Intelligence (AI) in medical field: An overview
Haleem, A., Javaid, M., & Khan, I. H. (2019) · Current Medicine Research and Practice · doi:10.1016/j.cmrp.2019.11.005 · Cited by 268
Jaafari, A., Panahi, M., Pham, B. T., Shahabi, H., Bui, D. T., Rezaie, F., & Lee, S. (2019) · CATENA · doi:10.1016/j.catena.2018.12.033 · Cited by 253
Metadata
- Authors
- Tien Bui, D., Bui, Q.-T., Nguyen, Q.-P., Pradhan, B., Nampak, H., & Trinh, P. T.
- Venue
- Agricultural and Forest Meteorology
- Publisher
- Elsevier BV
- Published
- 2017-02
- Volume
- 233
- Pages
- 32-44
- ISSN
- 0168-1923 (ISSN-L)
- OpenAlex
- W2557002900
- Cited by
- 391
- References
- 78
- FWCI
- 19.49
- Type
- journal article
- Language
- en
- Open access
- closed
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- This page
- CoChat. (2026). Citation check: A hybrid artificial intelligence approach using GIS-based neural-fuzzy inference system and particle swarm optimization for forest fire susceptibility modeling at a tropical area. https://app.cochat.ai/papers/10.1016/j.agrformet.2016.11.002
- The paper
- Tien Bui, D., Bui, Q.-T., Nguyen, Q.-P., Pradhan, B., Nampak, H., & Trinh, P. T. (2017). A hybrid artificial intelligence approach using GIS-based neural-fuzzy inference system and particle swarm optimization for forest fire susceptibility modeling at a tropical area. Agricultural and Forest Meteorology. https://doi.org/10.1016/j.agrformet.2016.11.002
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.
