TY - JOUR

T1 - Assessing Landslide Hazard Using Artificial Neural Network

T2 - case study of Mazandaran, Iran

A1 - Farrokhzad,Farzad

A1 - Choobbasti,Asskar Janalizadeh

A1 - Barari,Amin

A1 - Ibsen,Lars Bo

AU - Farrokhzad,Farzad

AU - Choobbasti,Asskar Janalizadeh

AU - Barari,Amin

AU - Ibsen,Lars Bo

PY - 2011

Y1 - 2011

N2 - Investigations of soil failures are subjects touching both geology and engineering. These investigations call the joint efforts of engineering geologists and geotechnical engineers. From the studies of field case records at least two types of soil failures have been distinguished, namely "shear failure" which is main concentration of the current research and "liquefaction failure". Shear failures along shear planes occur when the shear stress along the sliding surfaces exceed the effective shear strength. These slides have been referred to as landslide. An expert system based on artificial neural network has been developed for use in the stability evaluation of slopes under various geological conditions and engineering requirements. The Artificial neural network model of this research uses slope characteristics as input and leads to the output in form of the probability of failure and factor of safety. It can be stated that the trained neural networks are capable of predicting the stability of slopes and safety factor of landslide hazard in study area with an acceptable level of confidence. Landslide hazard analysis and mapping can provide useful information for catastrophic loss reduction, and assist in the development of guidelines for sustainable land use planning. The analysis is used to identify the factors that are related to landslides and to predict the landslide hazard in the future based on such a relationship.

AB - Investigations of soil failures are subjects touching both geology and engineering. These investigations call the joint efforts of engineering geologists and geotechnical engineers. From the studies of field case records at least two types of soil failures have been distinguished, namely "shear failure" which is main concentration of the current research and "liquefaction failure". Shear failures along shear planes occur when the shear stress along the sliding surfaces exceed the effective shear strength. These slides have been referred to as landslide. An expert system based on artificial neural network has been developed for use in the stability evaluation of slopes under various geological conditions and engineering requirements. The Artificial neural network model of this research uses slope characteristics as input and leads to the output in form of the probability of failure and factor of safety. It can be stated that the trained neural networks are capable of predicting the stability of slopes and safety factor of landslide hazard in study area with an acceptable level of confidence. Landslide hazard analysis and mapping can provide useful information for catastrophic loss reduction, and assist in the development of guidelines for sustainable land use planning. The analysis is used to identify the factors that are related to landslides and to predict the landslide hazard in the future based on such a relationship.

KW - Landslides

KW - Expert systems

KW - Artificial neural network

KW - Geology

KW - Mazandaran

KW - Landslides

KW - Expert systems

KW - Artificial neural network

KW - Geology

KW - Mazandaran

JO - Carpathian Journal of Earth and Environmental Sciences

JF - Carpathian Journal of Earth and Environmental Sciences

SN - 1842-4090

IS - 1

VL - 6

SP - 251

EP - 261

ER -