Performance evaluation neural network and logistic regression methods in predict the occurrence of mass movements in the upper of (Komanaj Chay basin)

samandar, nasrin; hejazi, Asadollah

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Volume 19, Issue 66 (9-2019)

جغرافیایی 2019, 19(66): 77-97

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Performance evaluation neural network and logistic regression methods in predict the occurrence of mass movements in the upper of (Komanaj Chay basin)

Nasrin Samandar ^*

¹, Asadollah Hejazi²

1- abriz university
2- tabriz university

Abstract: (5432 Views)

This study aimed to identify factors leading to slope instability, Maps preparation, determine potential areas mass movements and risk zoning in the Upper Basin Komanaj Chay. That is one of the important basins in the northern city of Tabriz, by Using logistic regression models and artificial neural network done. This basin due to topography, tectonics, geology, stratigraphy, and the climate is prone to a variety of slope instability, this phenomenon always occurs. According to the study variables such as altitude, slope, aspect, type of formation, distance to fault, distance from the river, land use, distance from the road, as the independent variable And distribution of unstable slopes as the dependent variable using logistic regression models and artificial neural network was analyzed .The results showed that the most important factors in the occurrence of slope instability in the basin are as follows: Elevation, distance from the river, lithology, faults, slope and aspect More than 50 percent of instability range in height from 1850 to 1520 in the study area dip 32-17 degrees, at a distance of 200 meters from the canal and 500 meters from the fault occurred. According to the results of a very high percentage of areas the risk of neural network and logistic regression models respectively 5.6 and 8.3 percent is the mainly areas close to the drainage network which includes the lithology of these areas are located in areas with lower resistance. Statistical methods logistics showed a lot of reflects of faults and lithology in this areas is based Landslide. Evaluation ROC indicator showed that the model was assessed using logistic regression model is 0.894 and neural network models is 0.826. In fact, both models show a high value and suggest that mass movement and slope instabilities observed a strong relationship with probability values derived from logistic regression models and artificial neural network model. The results of this study can be useful risk management slope instabilities and control is deteriorating factors.

Keywords: Logistic regression method, Neural network method, fuzzy modeling, landslides, upper of komanaj chay

Full-Text [PDF 1285 kb] (981 Downloads)

Type of Study: Research | Subject: Special
Received: 2017/02/12 | Accepted: 2017/11/29 | Published: 2019/09/1

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samandar N, hejazi A. Performance evaluation neural network and logistic regression methods in predict the occurrence of mass movements in the upper of (Komanaj Chay basin). جغرافیایی 2019; 19 (66) :77-97
URL: http://geographical-space.iau-ahar.ac.ir/article-1-2812-en.html

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