20 citations as recorded by crossref.

1. Comprehensive application of transfer learning, unsupervised learning and supervised learning in debris flow susceptibility mapping R. Gao et al. https://doi.org/10.1016/j.asoc.2024.112612
2. Medium-scale hazard mapping for shallow landslide initiation: the Buyukkoy catchment area (Cayeli, Rize, Turkey) H. Nefeslioglu et al. https://doi.org/10.1007/s10346-011-0267-7
3. A debris flow susceptibility mapping study considering sample heterogeneity R. Gao et al. https://doi.org/10.1007/s12145-024-01453-w
4. Adaptation and comparison of expert opinion to analytical hierarchy process for landslide susceptibility mapping M. Ercanoglu et al. https://doi.org/10.1007/s10064-008-0170-1
5. Application of Artificial Neural Networks in Assessing Mining Subsidence Risk Y. Kim & S. Lee https://doi.org/10.3390/app10041302
6. A comparative study on indirect determination of degree of weathering of granites from some physical and strength parameters by two soft computing techniques C. Gokceoglu et al. https://doi.org/10.1016/j.matchar.2009.06.006
7. Landslide susceptibility assessment in the İzmir (West Anatolia, Turkey) city center and its near vicinity by the logistic regression method C. Kıncal et al. https://doi.org/10.1007/s12665-009-0070-0
8. Predictive modelling for uranium content using artificial neural networks: a case study A. Padhi & D. Pande https://doi.org/10.1007/s10967-025-10368-9
9. An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps H. Nefeslioglu et al. https://doi.org/10.1016/j.enggeo.2008.01.004
10. Influence of seismic acceleration on landslide susceptibility maps: a case study from NE Turkey (the Kelkit Valley) H. Das et al. https://doi.org/10.1007/s10346-012-0342-8
11. Stability assessment of high-steep cut slope debris on a landslide (Gumushane, NE Turkey) A. Kaya et al. https://doi.org/10.1007/s10064-015-0753-6
12. Local site effects evaluation by surface wave and H/V survey methods in Senirkent (Isparta) region, southwestern Turkey M. Kanbur et al. https://doi.org/10.1007/s11803-020-0564-z
13. Comparison of different sampling strategies for debris flow susceptibility mapping: A case study using the centroids of the scarp area, flowing area and accumulation area of debris flow watersheds R. Gao et al. https://doi.org/10.1007/s11629-020-6471-y
14. Geohazard reconnaissance mapping for a settlement area N. Yesiloglu-Gultekin et al. https://doi.org/10.1007/s12665-011-0984-1
15. An assessment on the use of Terra ASTER L3A data in landslide susceptibility mapping H. Nefeslioglu et al. https://doi.org/10.1016/j.jag.2011.08.005
16. Utilization of the limit equilibrium and finite element methods for the stability analysis of the slope debris: An example of the Kalebasi District (NE Turkey) S. Alemdag et al. https://doi.org/10.1016/j.jafrearsci.2015.03.010
17. A Research on Cross-Regional Debris Flow Susceptibility Mapping Based on Transfer Learning R. Gao et al. https://doi.org/10.3390/rs14194829
18. A study on the development of an artificial neural network model for the prediction of ground subsidence over abandoned mines in Korea Y. Kim et al. https://doi.org/10.1080/12269328.2016.1254573
19. Prediction of ground subsidence in Samcheok City, Korea using artificial neural networks and GIS K. Kim et al. https://doi.org/10.1007/s00254-008-1492-9
20. Comparison of Different Negative-Sample Acquisition Strategies Considering Sample Representation Forms for Debris Flow Susceptibility Mapping R. Gao et al. https://doi.org/10.3390/app14209240