基于进化神经网络的深基坑支护结构位移反分析

Shengli Zhao, Yan Liu
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引用次数: 1

摘要

提出了一种深基坑支护结构位移反分析的进化神经网络方法,以寻找最优力学参数。首先,用BP网络取代耗时的有限元方法,建立深基坑支护结构的力学参数值与位移之间的非线性关系,然后采用遗传算法作为优化方法,在其全局范围内搜索最优力学参数。通过一个算例说明了该方法的应用,得到了合理的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Displacement back analysis on supporting structure of deep foundation pit based on evolutionary neural nrtwork
An evolutionary neural network method of displacement back analysis on supporting structure of deep foundation pit is proposed to search the optimal mechanical parameters. First, the BP network replaces the time-consuming finite element method to establish the non-linear relationship between the values of deep foundation pit mechanical parameters and displacement of its supporting structure, then genetic algorithm is used as an optimization method to search the optimal mechanical parameters in their global ranges. Application of this methodology is illustrated with a numerical example and reasonable results are yielded.
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