基于改进型变步长FOA-Richards模型的地铁工程沉降变形预测  

Prediction to Metro Engineering Subsidence and Deformation based on Improved FOA-Richards Model with Variable Step Size

作　　者：罗利娟[1] Luo Lijuan(School of Engineering and Technology,Xi’an Fanyi University,Xi’an Shaanxi 710105)

机构地区：[1]西安翻译学院工程技术学院,陕西西安710105

出　　处：《西安翻译学院论坛》2020年第3期59-63,共5页Forum of Xi'an Fanyi University

基　　金：西安翻译学院校级科研项目(19A03);区域经济与产业发展研究团队(XFU17KYTDC02)。

摘　　要：针对Ricaaras曲线预测模型参数估计较难的问题,研究一种改进型变步长果蝇优化算法,对基本果蝇优化算法进行步长改进和流程优化,并将Ricaaras模型的参数估计转化成一个四维约束函数优化问题。遵循“最小线性二乘”的准则,实现Ricaaras模型的参数估计,将该模型应用于某市地铁沉降观测点的沉降趋势预测。为进一步验证算法准确性和有效性,将改进型变步长果蝇优化算法(改进型VS-FOA)与粒子群算法(PSO)、遗传算法(GA)从预测精度和收敛速度两个维度进行对比分析,结果表明,用改进型VS-FOA算法估计的Ricaaras模型预测精度更高。In view of the difficulty of parameter estimation in the Richards curve prediction model,an im­proved fruit fly optimization algorithm was studied to improve the step size and to optimize the process,and the parameter estimation problem of Richards model was transformed into a four-dimensional constraint function opti­mization problem.Based on the principle of u linear least square method,parameter estimation of the Richards model was realized,and the model was applied to a city Metro engineering prediction.To further verify the ac­curacy and effectiveness of the algorithm,the improved VS-FOA algorithm was compared with the particle swarm optimization(PSO)algorithm and the genetic algorithm(GA)algorithm in two dimensions:prediction accuracy and convergence speed.The results show that the Richards model estimated by the improved VS-FOA algorithm has higher prediction accuracy.

关 键 词：改进型VS-FOA算法 Ricaaras模型 地铁沉降 预测精度 收敛速度 

分 类 号：U231.94[交通运输工程—道路与铁道工程]