Rainfall-induced landslide hazard assessment using artificial neural networks

2006 ◽  
Vol 31 (2) ◽  
pp. 235-247 ◽  
Author(s):  
H. B. Wang ◽  
K. Sassa
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Hazard Assessment ◽  
Landslide Hazard ◽  
Landslide Hazard Assessment ◽  
Artificial Neural

scholarly journals COMBINING NEURAL NETWORKS AND GEOSTATISTICS FOR LANDSLIDE HAZARD ASSESSMENT OF SAN SALVADOR METROPOLITAN AREA, EL SALVADOR

2017 ◽  
Vol 23 (1) ◽  
pp. 155-172
Author(s):  
Ricardo Ríos ◽  
Alexandre Ribó ◽  
Roberto Mejía ◽  
Giovanni Molina
Keyword(s):  
Neural Networks ◽  
Logistic Regression ◽  
El Salvador ◽  
Hazard Assessment ◽  
Slope Angle ◽  
Landslide Hazard ◽  
Assessment Model ◽  
Landslide Hazard Assessment ◽  
San Salvador ◽  
Geostatistical Approach

This contribution describes the creation of a landslide hazard assessment model for San Salvador, a department in El Salvador. The analysis started with an aerial photointerpretation from Ministry of Environment and Natural Resources of El Salvador (MARN Spanish acronym), where 4792 landslides were identified and georeferenced along with 7 conditioning factors including: geomorphology, geology, rainfall intensity, peak ground acceleration, slope angle, distance to road, and distance to geological fault. Artificial Neural Networks (ANN) were utilized to assess the susceptibility to landslides, achieving results where more than 80% of landslide were properly classified using in-sample and out of sample criteria. Logistic regression was used as base of comparison. Logistic regression obtained a lower performance. To complete the analysis we have performed interpolation of the points using the kriging method from geostatistical approach. Finally, the results show that is possible to derive a landslide hazard map, making use of a combination of ANNs and geostatistical techniques, thus the present study can help landslide mitigation in El Salvador.

Hazard assessment of organic chemicals with the use of artificial neural networks

2009 ◽  
Vol 43 (2) ◽  
pp. 212-217 ◽  
Author(s):  
I. V. Germashev ◽  
E. V. Derbisher ◽  
A. Yu. Aleksandrina ◽  
V. E. Derbisher
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Hazard Assessment ◽  
Organic Chemicals ◽  
Artificial Neural
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