摘要
The stability of underground opening is strongly constrained by a variety of factors. These include initial stress, structure of rock mass, and underground water, etc. A new approach proposed in this paper aims at revealing the degree of significance of them in order to catch the key factors. This new approach utilizes the mapping potentiality of artificial neural network and works out the sophisticated interactions among those factors from sample set. As a demonstration, an example is given for the application of this method to an underground opening. All results of this paper prove the efficiency of artificial neural network in stability analysis of underground opening.
The stability of underground opening is strongly constrained by a variety of factors. These include initial stress, structure of rock mass, and underground water, etc. A new approach proposed in this paper aims at revealing the degree of significance of them in order to catch the key factors. This new approach utilizes the mapping potentiality of artificial neural network and works out the sophisticated interactions among those factors from sample set. As a demonstration, an example is given for the application of this method to an underground opening. All results of this paper prove the efficiency of artificial neural network in stability analysis of underground opening.
关键词
人工神经网络
稳定性研究
岩石
数据处理
矿山
stability of underground opening
artificial neural networks
Relative Strength of Effect (RSE)
