基于案例推理的边坡稳定性评价系统及应用

Research on Slope Stability Evaluation System Based on Case-based Reasoning

探讨了基于案例推理技术在边坡稳定性评价中的应用,提出了边坡案例的表示、聚类索引、检索和调整模型,并运用Access建立了边坡案例库,设计并开发了基于案例推理的边坡稳定性评价系统,实现了遗传算法优化属性权重和欧式距离、类比分析及神经网络的3种检索方法,最后运用边坡工程实例对系统进行了验证。结果表明,该系统是合理有效的,对工程边坡稳定性评价将具有重要的理论意义和工程实用价值。

This paper discussed the application of techniques based on case-based reasoning （CBR） for slope stability evaluation. It put forward the representation, adjustment and retrieval model, in which Access data-base was used to represent and storage slope cases. The slope stability evaluation system using case-based reasoning was designed and programmed. In this system, genetic algorithm is used to optimize factors weight of critical slope, dynamic clustering technology is applied to index the case storage so as to improve the retrieval efficiency and three theories（ analogous analysis, neural network and Euclidean distance）were uesd to find out the best similar case in the storage. Practical engineering slopes were applied to test the system. The results show that the system is reasonable and feasible, which is of great academic significance and practical value for the stability evaluation and treatment in the slope engineering.