流离失所(心理学)
计算机科学
人工蜂群算法
支持向量机
算法
数学优化
人工智能
数学
心理学
心理治疗师
作者
Changxing Zhu,Hongbo Zhao,Ming Zhao
摘要
Accurate geomechanical parameters are critical in tunneling excavation, design, and supporting. In this paper, a displacements back analysis based on artificial bee colony (ABC) algorithm is proposed to identify geomechanical parameters from monitored displacements. ABC was used as global optimal algorithm to search the unknown geomechanical parameters for the problem with analytical solution. To the problem without analytical solution, optimal back analysis is time-consuming, and least square support vector machine (LSSVM) was used to build the relationship between unknown geomechanical parameters and displacement and improve the efficiency of back analysis. The proposed method was applied to a tunnel with analytical solution and a tunnel without analytical solution. The results show the proposed method is feasible.
科研通智能强力驱动
Strongly Powered by AbleSci AI