A platform for research: civil engineering, architecture and urbanism
Summary Rock behavior, such as the stability of underground openings, is controlled by many different factors which have varying levels of influence. It is very difficult to identify the relative effect of each factor with traditional methods, such as structural analysis and statistical approaches. This paper introduces a hierarchical analytical method based on the application of neural networks which reveals the different degrees of importance of these factors so as to recognize the key factors. This makes it possible to focus on the key factors and do rock engineering more efficiently. An example is given applying this approach to an underground opening.
Summary Rock behavior, such as the stability of underground openings, is controlled by many different factors which have varying levels of influence. It is very difficult to identify the relative effect of each factor with traditional methods, such as structural analysis and statistical approaches. This paper introduces a hierarchical analytical method based on the application of neural networks which reveals the different degrees of importance of these factors so as to recognize the key factors. This makes it possible to focus on the key factors and do rock engineering more efficiently. An example is given applying this approach to an underground opening.
A hierarchical analysis for rock engineering using artificial neural networks
1997
Article (Journal)
English
Local classification TIB:
560/4815/6545
BKL:
38.58
Geomechanik
/
56.20
Ingenieurgeologie, Bodenmechanik
A Hierarchical Analysis for Rock Engineering Using Artificial Neural Networks
British Library Online Contents | 1997
|A hierarchical analysis for rock engineering using artificial neural networks
Springer Verlag | 1997
|Applicability of artificial neural network in rock engineering
British Library Conference Proceedings | 2004
|Estimating Rock Cuttability using Regression Trees and Artificial Neural Networks
British Library Online Contents | 2009
|Estimating Rock Cuttability using Regression Trees and Artificial Neural Networks
Online Contents | 2008
|