Evaluation of slope stability based on case-based reasoning integrated with neural network

An evaluation approach to slope stability based on case-based reasoning integrated with neural network is presented. And in view of the complex and uncertainty of the information of slope stability evaluation, a model indexing slope base case with neural network is set up. In this model, the relationship of similarity between the slope base cases is established by the neural network through training based on case-based reasoning; and the most similar base case to the slope target case in the base cases of slope is found out. Finally, the slope stability of target case is evaluated. It is shown from examples that the result of stability evaluation of the slope is the same as the its practical state; and the approach is simple, practical, and convenient to use.