The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
Cited by
Rahmati, O., Pourghasemi, H. R., & Zeinivand, H. (2016) · Geocarto International · doi:10.1080/10106049.2015.1041559 · Cited by 632
Khosravi, K., Nohani, E., Maroufinia, E., & Pourghasemi, H. R. (2016) · Natural Hazards · doi:10.1007/s11069-016-2357-2 · Cited by 528
Hong, H., Panahi, M., Shirzadi, A., Ma, T., Liu, J., Zhu, A.-X., Chen, W., Kougias, I., & Kazakis, N. (2018) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.10.114 · Cited by 432
Mapping flood susceptibility in mountainous areas on a national scale in China
Zhao, G., Pang, B., Xu, Z., Yue, J., & Tu, T. (2018) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.10.037 · Cited by 389
Application of GIS-Interval Rough AHP Methodology for Flood Hazard Mapping in Urban Areas
Gigović, L., Pamučar, D., Bajić, Z., & Drobnjak, S. (2017) · Water · doi:10.3390/w9060360 · Cited by 341
Metadata
- Authors
- Kia, M. B., Pirasteh, S., Pradhan, B., Mahmud, A. R., Sulaiman, W. N. A., & Moradi, A.
- Venue
- Environmental Earth Sciences
- Published
- 2011-12-31
- Volume
- 67
- Issue
- 1
- Pages
- 251-264
- ISSN
- 1866-6280 (ISSN-L)
- 1866-6299
- OpenAlex
- W2027386095
- Cited by
- 692
- References
- 1
- FWCI
- 7.90
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. https://app.cochat.ai/papers/10.1007/s12665-011-1504-z
- The paper
- Kia, M. B., Pirasteh, S., Pradhan, B., Mahmud, A. R., Sulaiman, W. N. A., & Moradi, A. (2012). An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environmental Earth Sciences. https://doi.org/10.1007/s12665-011-1504-z
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.
