Analysis of Reservoir Slopes Based on Fuzzy Disturbance Ant-Cluster Algorithm

There are many factors affect the stability of reservoir slopes, each of them is associated and coupled with others. Generally, the analysis of slopes stability can be achieved by the method of effect-factors analogy and cluster analysis. Traditional cluster analysis is difficult to obtain the stable global optimal solution, since the results are sensitive to the initial cluster center and the order of sample input. Conventional ant colony clustering algorithm can get an appropriate result, by simulating the ants intelligent behavior of transportation. Consequently, in this paper a method of ant colony algorithm base on fuzzy disturbance is proposed which can gain the cluster analysis of reservoir slopes through guiding the ants cluster by the accumulation and change of ant pheromones. The results, compared with conventional cluster analysis method, simulated annealing algorithm method and conventional ant cluster algorithm method, shows that this method is effective and convenient to accomplish the analysis of reservoir slopes.