Volume 5, Issue 2 (4-2012)
2012, 5(2): 1269-1286 |
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:
soori S. Landslide hazard zonation using artificial neural networks A case study: Keshvari watershed (Nozhiyan). Journal of Engineering Geology 2012; 5 (2) :1269-1286
URL: http://jeg.khu.ac.ir/article-1-374-en.html
URL: http://jeg.khu.ac.ir/article-1-374-en.html
1- , soorisalman@yahoo.com
Abstract: (13120 Views)
The Keshvari watershed is located at south east of Khorramabad city in Lorestan province. This area is one part of the folded Zagros zone based on structural geology classification. By consider the type of geological formations, topographic conditions and its area, this watershed is very unstable and capable for occurring landslide. In this study, artificial neural network (ANN) with structure of multi-layer percepteron and Back Propagation learning algorithm used for zonation of landslide risk. The results of ANN showed the final structure of 9-11-1 for zonation of landslide risk in Keshvari watershed. According this zonation, 23.81, 7.53, 6.49, 18.68 and 43.47 percent of area are located in very low, low, moderate, high and very high risk classes, respectively.
Type of Study: Original Research |
Subject:
En. Ecosystem
Accepted: 2016/10/5 | Published: 2016/10/5
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. |
