The prediction of slope stability was performed using artificial neural networks (ANNs) in this work. The factor of safety determined by numerical analysis was used to develop ANN’s data sets. The inputs to the network are slope height, applied surcharge and slope angle. Correlation coefficients between numerical data and ANNs outputs showed the feasibility of ANNs for successfully modelling and predicting safety issues. The ANNs training phase is improved using a genetic algorithm (GA), and the results are compared to those obtained without GA trained ANNs. A sensitivity analysis is conducted to ascertain the relative contribution of different factors on slope stability. The slope angle and applied surcharge have a significant effect on sl...
This paper is concerned principally with the application of ANN model in geotechnical engineering. I...
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...
Slope stability analysis is one of the most important problems in geotechnical engineering. The deve...
This paper presents the slope stability for road embankment constructed on the soft ground treated w...
This paper details the utilization of artificial intelligence (AI) in the field of slope stability w...
In present paper, authors develop a model for estimation of earth slope stability based on the artif...
The evaluation and precise prediction of safety factor (SF) of slopes can be useful in designing/ana...
The surface of the earth is very rarely flat and so there are slopes nearly everywhere. The loads on...
To enable assess slope stability problems efficiently, various machine learning algorithms have been...
Slope engineering is a type of complex system engineering that is mostly involved in water conservan...
Keeping large-scale transportation infrastructure networks, such as railway net-works, operational u...
AbstractThis study deals with the development of Artificial Neural Network (ANN) and Multiple Regres...
The stability of slopes is always under severe threats in many parts of Western Ghats, especially in...
The purpose of this article is to demonstrate the application of probabilistic neural networks (PNNs...
This paper is concerned principally with the application of ANN model in geotechnical engineering. I...
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...
Slope stability analysis is one of the most important problems in geotechnical engineering. The deve...
This paper presents the slope stability for road embankment constructed on the soft ground treated w...
This paper details the utilization of artificial intelligence (AI) in the field of slope stability w...
In present paper, authors develop a model for estimation of earth slope stability based on the artif...
The evaluation and precise prediction of safety factor (SF) of slopes can be useful in designing/ana...
The surface of the earth is very rarely flat and so there are slopes nearly everywhere. The loads on...
To enable assess slope stability problems efficiently, various machine learning algorithms have been...
Slope engineering is a type of complex system engineering that is mostly involved in water conservan...
Keeping large-scale transportation infrastructure networks, such as railway net-works, operational u...
AbstractThis study deals with the development of Artificial Neural Network (ANN) and Multiple Regres...
The stability of slopes is always under severe threats in many parts of Western Ghats, especially in...
The purpose of this article is to demonstrate the application of probabilistic neural networks (PNNs...
This paper is concerned principally with the application of ANN model in geotechnical engineering. I...
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...