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Assessing Landslide Hazard Using Artificial Neural Network:case study of Mazandaran, Iran

By Farzad Farrokhzad, Asskar Janalizadeh Choobbasti, Amin Barari and Lars Bo Ibsen

Abstract

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.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

Topics: Landslides, Expert systems, Artificial neural network, Geology, Mazandaran, Landslides, Expert systems, Artificial neural network, Geology, Mazandaran
Year: 2011
OAI identifier: oai:pure.atira.dk:publications/ead9cce2-eac2-428f-a302-9fafe8187177
Provided by: VBN
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