35 citations as recorded by crossref.

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3. Landslide Susceptibility Mapping in North Tehran, Iran: Linear Regression, Neural Networks, and Fuzzy Logic Approaches A. Ghaedi Vanani et al. 10.1007/s10706-024-02920-3
4. Assessment of landslides induced by earthquake risk of Istanbul: A comprehensive study utilizing an integrated DFS-AHP and DFS-EDAS approach B. Yalcin Kavus & A. Taskin 10.1016/j.soildyn.2025.109285
5. Natural Laboratories for Field Observation About Genesis and Landscape Effects of Palaeo-Earthquakes: a Proposal for the Rocca Busambra and Monte Barracù Geosites (West Sicily) L. Basilone et al. 10.1007/s12371-018-0334-8
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7. Comparing data-driven landslide susceptibility models based on participatory landslide inventory mapping in Purwosari area, Yogyakarta, Java G. Samodra et al. 10.1007/s12665-017-6475-2
8. Introducing a novel multi-layer perceptron network based on stochastic gradient descent optimized by a meta-heuristic algorithm for landslide susceptibility mapping H. Hong et al. 10.1016/j.scitotenv.2020.140549
9. Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM J. Dou et al. 10.3390/rs11060638
10. Predicting the landslides triggered by the 2009 96E/Ida tropical storms in the Ilopango caldera area (El Salvador, CA): optimizing MARS-based model building and validation strategies E. Rotigliano et al. 10.1007/s12665-019-8214-3
11. Optimizing slope unit-based landslide susceptibility mapping using the priority-flood flow direction algorithm G. Yan et al. 10.1016/j.catena.2023.107657
12. Combining Evolutionary Algorithms and Machine Learning Models in Landslide Susceptibility Assessments W. Chen et al. 10.3390/rs12233854
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20. A three-stage and multi-objective stochastic programming model to improve the sustainable rescue ability by considering secondary disasters in emergency logistics J. Zhang et al. 10.1016/j.cie.2019.02.003
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22. Spatiotemporal Landslide Susceptibility Mapping Incorporating the Effects of Heavy Rainfall: A Case Study of the Heavy Rainfall in August 2021 in Kitakyushu, Fukuoka, Japan J. Li et al. 10.3390/w13223312
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26. A comparison of slope units and grid cells as mapping units for landslide susceptibility assessment Q. Ba et al. 10.1007/s12145-018-0335-9
27. GIS-based landslide susceptibility assessment using statistical models: a case study from Souk Ahras province, N-E Algeria F. Mahdadi et al. 10.1007/s12517-018-3770-5
28. Macrobenthos habitat potential mapping using GIS-based artificial neural network models S. Lee et al. 10.1016/j.marpolbul.2012.10.023
29. Spatial clustering and modelling for landslide susceptibility mapping in the north of the Kathmandu Valley, Nepal B. Pokharel et al. 10.1007/s10346-020-01558-5
30. Landslide susceptibility mapping at Ovacık-Karabük (Turkey) using different artificial neural network models: comparison of training algorithms A. Can et al. 10.1007/s10064-017-1034-3
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33. Application of a hybrid model of neural networks and genetic algorithms to evaluate landslide susceptibility H. Wang et al. 10.1186/s40677-017-0076-y
34. Multiobjective Emergency Resource Allocation under the Natural Disaster Chain with Path Planning F. Wang et al. 10.3390/ijerph19137876
35. Landslide susceptibility assessment in the Hoa Binh province of Vietnam: A comparison of the Levenberg–Marquardt and Bayesian regularized neural networks D. Tien Bui et al. 10.1016/j.geomorph.2012.04.023