基于案例挖掘的边坡稳定性智能评价系统研究

虽然边坡灾害治理实践已经积累了大量的成功的或失败的边坡治理工程案例，但这些工程案例产生的大量数据信息未被充分利用与开发，造成了极大的资源浪费。为此，基于边坡工程案例，应用数据挖掘与知识发现和递归的自-组织模糊神经推理网络的方法，初步提出了一种基于案例挖掘的边坡稳定性智能评价系统，并通过案例挖掘的应用实例表明了该系统的有效性和可行性。

Study on intelligent evaluation system of slope stability based on case mining

Slope hazard is a serious natural hazard next only to earthquake and floodwater. It has brought about great losses to the economic and social development worldwide. Each year it causes a loss up to billions of dollars in the whole world. A striking amount of money has been spent on the prevention and redress of the hazard; and much more losses have been incurred indirectly in addition. Many slope treatment cases have been already accumulated for over a long time of slope treatment, but much data information of these slope cases are not completely used and developed, which results in huge resources waste. For this reason, applying the methods of the data mining, knowledge discovery in databases and recurrent self-organizing neural fuzzy inference network, an intelligent evaluation system of slope stability based on case mining is presented. Meanwhile, practical applications illustrate validity and feasibility of the system.