Landslide Susceptibility Analysis with Artificial Neural Networks Used in a GIS Environment
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-47079-0_65
Reference4 articles.
1. Gentilucci, M., Materazzi, M., & Pambianchi, G. (2021). Statistical analysis of landslide susceptibility, Macerata province (Central Italy). Hydrology, 8(1), 5.
2. Lucianetti, G., Mastrorillo, L., Mazza, R., & Partel, P. (2019).Groundwater response to precipitation extremes: the case of the “Vaia” storm (Eastern Italian Alps). Acque Sotterranee-Italian Journal of Groundwater, 8(4). https://doi.org/10.7343/as-2019-429
3. Park, S., Choi, C., Kim, B., & Kim, J. (2013). Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area. Korea. Environmental Earth Sciences, 68(5), 1443–1464.
4. Sarkar, S., & Kanungo, D. P. (2004). An integrated approach for landslide susceptibility mapping using remote sensing and GIS. Photogrammetric Engineering & Remote Sensing, 70(5), 617–625.
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