Assessment, Categorisation and Prediction of the Landslide-Affected Regions Using Soft Computing and Clustering Techniques
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s40031-023-00876-1.pdf
Reference123 articles.
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3. B. Pradhan, S. Lee, Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling. Environ. Model. Softw. 25(6), 747–759 (2010)
4. P. Biswajeet, L. Saro, The utilisation of optical remote sensing data and GIS tools for regional landslide hazard analysis using an artificial neural network model. Earth Sci. Front. 14(6), 143–151 (2007)
5. G. Martelloni, S. Segoni, R. Fanti, F. Catani, Rainfall thresholds for the forecasting of landslide occurrence at regional scale. Landslides 9(4), 485–495 (2012)
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