The isolation of landslide-prone territory using the neural network method
Authors:
About authors
- post-graduate student National Mineral Resources University (Mining University)
Abstract
The method neural networks of back propagation is discussed in this paper. Parameters of the original data for zoning and structure of the neural network are defined. It shows the results and assessments of accuracy landslide areas identification within Krasnaya Polyana. Proposal on the use of digital elevation models produced with high-precision geodetic techniques to improve the reliability of the simulation results is made.
Область исследования:
(Archived) Engineering geodesy
Funding:
None
References
- Russell S., Norvig P. Artificial Intelligence: A Modern Approach. Moscow: Ltd «I.D.Williams», 2006. 1424 p.
- Haykin S. Neural networks: a complete course: Translation from English. Moscow: Ltd «I.D. Williams», 2006. 1104 p.
- Pradhan B., Lee S. Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modeling // Environmental Modelling & Software. 2010. P.747-759.
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