Volume 1, Issue 2 (انگلیسی از صفحه 193 تا 208 2003)
2003, 1(2): 179-193 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Landslide Hazard Zonation Using Artificial Neural Network in the Talesh Area. Journal of Engineering Geology 2003; 1 (2) :179-193
URL: http://jeg.khu.ac.ir/article-1-310-en.html
URL: http://jeg.khu.ac.ir/article-1-310-en.html
Abstract: (6728 Views)
(Paper pages 179-192) Artificial Neural Network (ANN), has many abilities which have increade its application in different fields of engineering and geosciences. In this paper, the application of ANN in geological engineering(prediction of landslide hazard) in Talesh area, north of Iran, is evaluated. The results are shown that, the system is able to process input data by selecting effective parameters of landslide and give the landslide hazard potential as a ANN output. By considering the landslide hazard zonation map of the area and by using the ANN system, it becomes clear that, the Talesh area is a landslide hazard prone area. The most effective factors of slope instability of the area, are land use and land cover conditions, ground water and surface water effects, river erosion and tectonics activities.
Accepted: 2016/10/5 | Published: 2016/10/5
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
