... Abstract The aim of this paper is to present a practical application of Fuzzy Controllers and Artificial Neural Networks (ANN) models to analyze the stability of rock slopes defined by unfilled discontinuities. Results from direct shear tests on different boundary conditions and types...

... chainage, and an Artificial Neural Network (ANN) that was trained, validated and tested on the outputs of the BBN. The ANN demonstrated reasonable strength for fitting the BBN classifications, achieving an average overall accuracy of approximately 80%. This paper aims to draw a comparison between these two...

... compares the performance of two kinds of Artificial Neural Networks (ANN) - a Multilayer Perceptron (MLP) vs. a Long-Short-Term Memory (LSTM) Network - for this task. The data originates from the exploratory tunnel Ahrental " Pfons of the Brenner Base Tunnel which is currently under construction. The goal...

... of the different rock matrix based on the laboratory results and it's observed that the artificial neural network gives good result with higher accuracy than the conventional correlation methods. 1 INTRODUCTION Rock is different than the other engineering materials, cause its contains major discontinuities...

.... Self organising maps, are a special type of unsupervised artificial neural networks, which can learn from complex, multidimensional data, and transform them to visually decipherable clusters. The proposed, coding of the GIM, is performed through the combined use of scatter plots produced through, (SOM...

... of subjectivity often inherent in commonly used classification systems. These challenges are especially exacerbated in weak rock or densely jointed rock masses. This paper introduces a new approach to characterise densely jointed rock mass using artificial neural networks and principal component analysis, based...

... between elasticity and deformation modulus. In this paper, the relation between elasticity and Asmari deformation modulus obtained from the 5th cycle of plate load test has been employed. Then, by utilizing artificial neural network, an equation for predicting deformation modulus of Asmari formation...

... ABSTRACT This paper discusses the parameter identification and subsidence prediction by Artificial Neural Network and FEM database for design and construction of NATM. This paper describes two ANN models. The first is an optimal ANN model for parameter identification and the second...

... coal type neural network artificial neural network coal seam hydraulic leg friction angle longwall face longwall panel 11th Congress of the International Society for Rock Mechanics Ribeiro e Sousa, Olalla & Grossmann (eds) © 2007 Taylor & Francis Group, London, ISBN 978-0-415-45084-3...

... ABSTRACT: This paper describes an integrated approach of artificial neural network and expert system to the preliminary design of tunnels and slopes. Four neural network models and three expert systems are combined into an integrated system and driven under the same user interface. First two...

... ABSTRACT: In this paper it is shown how pre-peak, peak and post-peak deformability behaviour over a wide range of confining stresses can be encapsulated within a single multilayer feed forward artificial neural network. Data used to train the ‘artificial neural network is derived from...