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:: Volume 5, Issue 2 (4-2012) ::
2012, 5(2): 1269-1286 Back to browse issues page
Landslide hazard zonation using artificial neural networks A case study: Keshvari watershed (Nozhiyan)
Salman Soori *1
1- , soorisalman@yahoo.com
Abstract:   (11308 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.
Keywords: Landslide, zonation, Keshvari watershed, Artificial neural network
Full-Text [PDF 2844 kb]   (2976 Downloads)    
Type of Study: Research Paper | Subject: En. Ecosystem
Accepted: 2016/10/5 | Published: 2016/10/5
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soori S. Landslide hazard zonation using artificial neural networks A case study: Keshvari watershed (Nozhiyan). Journal title 2012; 5 (2) :1269-1286
URL: http://jeg.khu.ac.ir/article-1-374-en.html


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Volume 5, Issue 2 (4-2012) Back to browse issues page
نشریه زمین شناسی مهندسی Journal of Engineering Geology
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