Comparative analysis of multiple conventional neural networks for landslide susceptibility mapping
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s11069-022-05570-x.pdf
Reference112 articles.
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3. Aslam B et al (2021) Development of integrated deep learning and machine learning algorithm for the assessment of landslide hazard potential. Soft Comput 25(21):13493–13512
4. Aslam B et al (2022) Comparison of multiple conventional and unconventional machine learning models for landslide susceptibility mapping of Northern part of Pakistan. Environ, Develop Sustain: 1–28
5. Bacha AS et al (2018) Landslide inventory and susceptibility modelling using geospatial tools, in Hunza-Nagar valley, northern Pakistan. J Mt Sci 15(6):1354–1370
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