Slope stability analysis is one of the most important problems in geotechnical engineering. The development in slope stability analysis has followed the development in computational geotechnical engineering. This paper discusses the application of different recently developed artificial neural network models to slope stability analysis based on the actual slope failure database available in the literature. Different ANN models are developed to classify the slope as stable or unstable (failed) and to predict the factor of safety. The developed ANN model is found to be efficient compared with other methods like support vector machine and genetic programming available in literature. Prediction models are presented based on the developed ANN mo...
This paper presents the slope stability for road embankment constructed on the soft ground treated w...
This study aims to develop a tool able to help decision makers to find the best strategy for slopes ...
The present paper focuses on designing an artificial neural network (ANN) model and a multiple regre...
Slope stability analysis is one of the most important problems in geotechnical engineering. The deve...
The prediction of slope stability was performed using artificial neural networks (ANNs) in this work...
In present paper, authors develop a model for estimation of earth slope stability based on the artif...
This paper details the utilization of artificial intelligence (AI) in the field of slope stability w...
AbstractThis study deals with the development of Artificial Neural Network (ANN) and Multiple Regres...
The evaluation and precise prediction of safety factor (SF) of slopes can be useful in designing/ana...
Over the years, machine learning, which is a well-known method in artificial intelligent (AI) field ...
To enable assess slope stability problems efficiently, various machine learning algorithms have been...
Slope stability is the most important stage in the stabilization process for different scale slopes,...
Artificial Neural Network (ANN) such as backpropagation learning algorithm has been successfully use...
The surface of the earth is very rarely flat and so there are slopes nearly everywhere. The loads on...
With the advent of technology and the introduction of computational intelligent methods, the predict...
This paper presents the slope stability for road embankment constructed on the soft ground treated w...
This study aims to develop a tool able to help decision makers to find the best strategy for slopes ...
The present paper focuses on designing an artificial neural network (ANN) model and a multiple regre...
Slope stability analysis is one of the most important problems in geotechnical engineering. The deve...
The prediction of slope stability was performed using artificial neural networks (ANNs) in this work...
In present paper, authors develop a model for estimation of earth slope stability based on the artif...
This paper details the utilization of artificial intelligence (AI) in the field of slope stability w...
AbstractThis study deals with the development of Artificial Neural Network (ANN) and Multiple Regres...
The evaluation and precise prediction of safety factor (SF) of slopes can be useful in designing/ana...
Over the years, machine learning, which is a well-known method in artificial intelligent (AI) field ...
To enable assess slope stability problems efficiently, various machine learning algorithms have been...
Slope stability is the most important stage in the stabilization process for different scale slopes,...
Artificial Neural Network (ANN) such as backpropagation learning algorithm has been successfully use...
The surface of the earth is very rarely flat and so there are slopes nearly everywhere. The loads on...
With the advent of technology and the introduction of computational intelligent methods, the predict...
This paper presents the slope stability for road embankment constructed on the soft ground treated w...
This study aims to develop a tool able to help decision makers to find the best strategy for slopes ...
The present paper focuses on designing an artificial neural network (ANN) model and a multiple regre...