Abstract
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.
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