The isolation of landslide-prone territory using the neural network method
Authors:
About authors
- 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.
References
- Рассел С. Искусственный интеллект: современный подход / С.Рассел, П.Норвиг. М.: ООО «И.Д.Вильямс», 2006. 1424 с.
- Хайкин С. Нейронные сети: полный курс: Пер. с англ. М.: ООО «И.Д.Вильямс», 2006. 1104 с.
- Pradhan B. Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modeling / B.Pradhan, S.Lee. // Environmental Modelling & Software, 2010. Р.747-759.
Similar articles
Application of terrestrial laser scanning for creation of three-dimensional models of Shukhov tower
2013 V. A. Valkov, M. G. Mustafin, G. V. Makarov
Geodesic support of construction of cable-stayed bridges in the city Vladivostok
2013 E. S. Bogomolova, M. Ya. Bryn, V. N. Ivanov, D. V. Krashenitsin, A. A. Nikitchin, O. P. Sergeev, E. G. Tolstov
Connection content and properties of coal for quality control and quantity of coal-mining
2013 R. A. Takranov
Influence condition of ground on complexity in the process open pit Kuzbas`s coal deposits
2013 R. A. Takranov, A. A. Litvinova