岩体边坡滑移的系统学预报研究

Application of Systematological Theory to Landslide Prediction

滑坡灾害已成为全世界公认的三大地质灾害之一,以中国为例,每年由于滑坡而造成的经济损失高达200亿元左右,为此,滑坡引起了世界范围内的高度重视.然而,由于边坡岩体经常与传统概念中的均匀、连续介质之间存在明显差异,使得用传统连续介质力学方法计算边坡稳定性误差很大.事实上,岩体边坡作为一种复杂的地质体,是一个不断变化发展的地质系统,因此系统科学方法被引入岩体力学.该文结合作者本人的工程实践,将非等距时间序列灰色预测方法、协同学方法、神经网络方法和模糊神经网络等应用于岩体高边坡失稳过程分析和稳定性预测,并对它们的适用范围和应用效果进行了分析.该文还分析了边坡稳定性系统预测中应该解决的一些问题.

Landslide is one of the three serious geological disasters. In China the economic loss due to landslide amounts up to 20 billion Yuan every year. Since there are significant differences between the discontinuous rock masses and normal continuous materials, calculation of the stability of rock slopes using the conventional dynamical methods for continuous media is inaccurate. In fact, rock slopes are complicated geological masses that develop constantly. Therefore systematological methods are appli-(cable) to rock mechanics. In this paper, non-isometric time series gray prediction method, synergetic method, and radial basis function neural network method are applied to the slide prediction of slopes. The effects and applicable ranges of the above-mentioned methods are studied, and some other pro-blems in landslide prediction are also analyzed.