0000000000520016

AUTHOR

Antonino Scarbaci

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Strategies investigation in using artificial neural network for landslide susceptibility mapping: application to a Sicilian catchment

2013

Susceptibility assessment of areas prone to landsliding remains one of the most useful approaches in landslide hazard analysis. The key point of such analysis is the correlation between the physical phenomenon and its triggering factors based on past observations. Many methods have been developed in the scientific literature to capture and model this correlation, usually within a geographic information system (GIS) framework. Among these, the use of neural networks, in particular the multi-layer perceptron (MLP) networks, has provided successful results. A successful application of the MLP method to a basin area requires the definition of different model strategies, such as the sample selec…

HydrologyArtificial Neural NetworkAtmospheric Sciencegeographygeography.geographical_feature_categoryGeographic information systemArtificial neural networkComputer sciencebusiness.industrySettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaDrainage basinLandslideScientific literatureHazard analysisStructural basinGeotechnical Engineering and Engineering GeologyPerceptronGISArtificial Neural Network; GIS; Landslide Susceptibility MappingbusinessCartographyCivil and Structural EngineeringWater Science and TechnologyLandslide Susceptibility Mapping
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