基于PSO-PP的围岩稳定性评价

围岩的稳定性评价是一个复杂的不确定系统问题。结合投影寻踪方法、粒子群算法和逻辑斯谛曲线函数,建立了围岩稳定性评价的粒子群优化投影寻踪(projection pursuit based on particle swarm optimization,PSO-PP)模型。该模型一方面采用粒子群算法优化投影指标函数及逻辑斯谛曲线函数参数,确保了模型的准确性;另一方面利用逻辑斯谛曲线函数建立投影值与经验等级之间的非线性关系。模型的测试结果显示了良好的精度,实例分析结果与实际状态完全一致,表明该模型在围岩稳定性评价中的可行性和有效性。

Projection pursuit based on particle swarm optimization for evaluation of surrounding rock stability

Evaluation of surrounding rock stability is a complex system problem of uncertainty. Based on the projection pursuit (PP), the particle swarm optimization (PSO) and the logistic curve function (LCF), a new model for evaluation of surrounding rock stability is developed, which is referred as projection pursuit based on particle swarm optimization (PSO-PP). The model, on the one hand, uses PSO to optimize the projection index function and the parameters of LCF so as to ensure the accuracy of the parameters used in the model; on the other hand, the nonlinear relationship between projection values and experiential grades is established according to LCF. The test result of the model indicates there is a very good precision. In this study, the evaluation result obtained by applying the model developed here to an underground project is well consistent with the real situation. It is shown that the model here is feasible and effective in evaluating surrounding rock stability.