蚁群优化算法
理论(学习稳定性)
曲面(拓扑)
蚂蚁
边坡稳定性
边坡稳定性分析
岩土工程
地质学
计算机科学
数学
生物
数学优化
生态学
几何学
机器学习
作者
K.S. Kahatadeniya,Pruettha Nanakorn,K.M. Neaupane
标识
DOI:10.1016/j.enggeo.2009.06.010
摘要
Abstract Slope stability analysis of any natural or artificial slope aims at determining the factor of safety of the slip surface that possesses the lowest factor of safety. In this study, an ant colony optimization (ACO) algorithm is developed to solve this factor-of-safety minimization problem. Factors of safety of slip surfaces are found by using the Morgenstern–Price method, which satisfies both force and moment equilibrium. Nonlinear equations from the Morgenstern–Price method are solved numerically by the Newton–Raphson method. In the proposed ACO algorithm, the initiation point and the shape of the slip surface are treated as the search variables. The proposed heuristic algorithm represents slip surfaces as piecewise-linear curves and solves for the optimal curve yielding the minimum factor of safety. To demonstrate its applicability and to investigate the validity and effectiveness of the algorithm, four examples with varying complexity are presented. The obtained results are compared with the available literature and are found to be in agreement.
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