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.
Similar articles
Geomechanical analysis of surface settlement trough development due to construction of deep underground pillar station
2013 P. A. Demenkov
Ultrasonic control of the nonlinear elastic properties of the microcrumbling polycrystalline rocks
2013 V. M. Tsaplev, R. M. Ivanyuk, V. V. Zverevich
Modeling of work of elements of the combined box-shaped and pile base in weak soil
2013 D. A. Potyomkin, P. A. Demenkov
Development of land relations in the Vyborg district, Leningrad region in 1944-2012 years
2013 P. S. Tukalenko, V. F. Kovyazin