基于改进的粒子群优化算法的边坡可靠度分析

考虑边坡稳定性受多种随机因素影响,借鉴当前研究成果,尝试建立一种将随机因素和确定因素分别考虑的新的边坡可靠性分析模型,借助演化计算技术之一的粒子群优化算法收敛快和精度高的优点,通过设置影响其收敛速度的惯性因子,提高算法的收敛速度和精度,进行边坡最小可靠度指标的求解,并进行临界滑动面的搜索.研究成果表明,与其它方法比较,该方法具有较高的精确度和实用价值.

Analysis of Slope Reliability Based on Improved Particle Swarm Optimization Algorithms

Considering the slope stability affected by a variety of random factors,based on current research results,the new slope reliability analysis model which made the random factors and to specific factors considering respectively was to be set up.Particle Swarm Optimization algorithms,one of the evolution computing technologies was introduce to calculate the reliability index and search the critical slip surface because of its faster convergence speed and accuracy.When calculating,the important parameter called inertia factor was set to exponential function form which can improve the convergence speed and accuracy.Research results indicated that compared with other methods,this method has higher accuracy and faster convergence.Also,this study provides a new approach to analyze the reliability of slopes.